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apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/predictor/predictor_manager_test.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/predictor_manager.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/container/container_manager.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/evaluator_manager.h"
namespace apollo {
namespace prediction {
using apollo::common::adapter::AdapterConfig;
class PredictorManagerTest : public KMLMapBasedTest {
public:
void SetUp() override {
std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
ACHECK(cyber::common::GetProtoFromFile(file, &perception_obstacles_));
container_manager_.reset(new ContainerManager());
evaluator_manager_.reset(new EvaluatorManager());
predictor_manager_.reset(new PredictorManager());
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
common::adapter::AdapterManagerConfig adapter_conf_;
PredictionConf prediction_conf_;
std::unique_ptr<ContainerManager> container_manager_;
std::unique_ptr<EvaluatorManager> evaluator_manager_;
std::unique_ptr<PredictorManager> predictor_manager_;
};
TEST_F(PredictorManagerTest, General) {
FLAGS_enable_trim_prediction_trajectory = false;
std::string conf_file = "modules/prediction/testdata/adapter_conf.pb.txt";
bool ret_load_conf =
cyber::common::GetProtoFromFile(conf_file, &adapter_conf_);
EXPECT_TRUE(ret_load_conf);
EXPECT_TRUE(adapter_conf_.IsInitialized());
container_manager_->Init(adapter_conf_);
evaluator_manager_->Init(prediction_conf_);
predictor_manager_->Init(prediction_conf_);
auto obstacles_container =
container_manager_->GetContainer<ObstaclesContainer>(
AdapterConfig::PERCEPTION_OBSTACLES);
CHECK_NOTNULL(obstacles_container);
obstacles_container->Insert(perception_obstacles_);
auto adc_trajectory_container =
container_manager_->GetContainer<ADCTrajectoryContainer>(
AdapterConfig::PLANNING_TRAJECTORY);
evaluator_manager_->Run(adc_trajectory_container, obstacles_container);
predictor_manager_->Run(perception_obstacles_, adc_trajectory_container,
obstacles_container);
const PredictionObstacles& prediction_obstacles =
predictor_manager_->prediction_obstacles();
EXPECT_EQ(prediction_obstacles.prediction_obstacle_size(), 1);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/predictor/predictor_manager.h
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Use predictor manager to manage all predictors
*/
#pragma once
#include <map>
#include <memory>
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/predictor/predictor.h"
#include "modules/prediction/proto/prediction_conf.pb.h"
/**
* @namespace apollo::prediction
* @brief apollo::prediction
*/
namespace apollo {
namespace prediction {
class PredictorManager {
public:
/**
* @brief Constructor
*/
PredictorManager();
/**
* @brief Destructor
*/
virtual ~PredictorManager() = default;
/**
* @brief Initializer
* @param Prediction config
*/
void Init(const PredictionConf& config);
/**
* @brief Get predictor
* @return Pointer to the predictor
*/
Predictor* GetPredictor(const ObstacleConf::PredictorType& type);
/**
* @brief Execute the predictor generation
* @param Adc trajectory container
* @param Obstacles container
*/
void Run(const apollo::perception::PerceptionObstacles& perception_obstacles,
const ADCTrajectoryContainer* adc_trajectory_container,
ObstaclesContainer* obstacles_container);
/**
* @brief Predict a single obstacle
* @param A pointer to adc_trajectory_container
* @param A pointer to the specific obstacle
* @param A pointer to the obstacles container
* @param A pointer to prediction_obstacle
*/
void PredictObstacle(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container,
PredictionObstacle* const prediction_obstacle);
/**
* @brief Get prediction obstacles
* @return Prediction obstacles
*/
const PredictionObstacles& prediction_obstacles();
private:
/**
* @brief Register a predictor by type
* @param Predictor type
*/
void RegisterPredictor(const ObstacleConf::PredictorType& type);
/**
* @brief Create a predictor by type
* @param Predictor type
* @return A unique pointer to the predictor
*/
std::unique_ptr<Predictor> CreatePredictor(
const ObstacleConf::PredictorType& type);
/**
* @brief Register all predictors
*/
void RegisterPredictors();
void PredictObstacles(
const apollo::perception::PerceptionObstacles& perception_obstacles,
const ADCTrajectoryContainer* adc_trajectory_container,
ObstaclesContainer* obstacles_container);
void PredictObstaclesInParallel(
const apollo::perception::PerceptionObstacles& perception_obstacles,
const ADCTrajectoryContainer* adc_trajectory_container,
ObstaclesContainer* obstacles_container);
void InitVehiclePredictors(const ObstacleConf& conf);
void InitCyclistPredictors(const ObstacleConf& conf);
void InitDefaultPredictors(const ObstacleConf& conf);
void RunVehiclePredictor(
const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle, ObstaclesContainer* obstacles_container);
void RunPedestrianPredictor(
const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle, ObstaclesContainer* obstacles_container);
void RunCyclistPredictor(
const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle, ObstaclesContainer* obstacles_container);
void RunDefaultPredictor(
const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle, ObstaclesContainer* obstacles_container);
void RunEmptyPredictor(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container);
private:
std::map<ObstacleConf::PredictorType, std::unique_ptr<Predictor>> predictors_;
ObstacleConf::PredictorType vehicle_on_lane_predictor_ =
ObstacleConf::LANE_SEQUENCE_PREDICTOR;
ObstacleConf::PredictorType vehicle_off_lane_predictor_ =
ObstacleConf::FREE_MOVE_PREDICTOR;
ObstacleConf::PredictorType vehicle_in_junction_predictor_ =
ObstacleConf::LANE_SEQUENCE_PREDICTOR;
ObstacleConf::PredictorType cyclist_on_lane_predictor_ =
ObstacleConf::LANE_SEQUENCE_PREDICTOR;
ObstacleConf::PredictorType cyclist_off_lane_predictor_ =
ObstacleConf::FREE_MOVE_PREDICTOR;
ObstacleConf::PredictorType pedestrian_predictor_ =
ObstacleConf::FREE_MOVE_PREDICTOR;
ObstacleConf::PredictorType default_on_lane_predictor_ =
ObstacleConf::LANE_SEQUENCE_PREDICTOR;
ObstacleConf::PredictorType default_off_lane_predictor_ =
ObstacleConf::FREE_MOVE_PREDICTOR;
ObstacleConf::PredictorType vehicle_on_lane_caution_predictor_ =
ObstacleConf::MOVE_SEQUENCE_PREDICTOR;
ObstacleConf::PredictorType vehicle_in_junction_caution_predictor_ =
ObstacleConf::INTERACTION_PREDICTOR;
ObstacleConf::PredictorType vehicle_default_caution_predictor_ =
ObstacleConf::EXTRAPOLATION_PREDICTOR;
ObstacleConf::PredictorType vehicle_interactive_predictor_ =
ObstacleConf::EMPTY_PREDICTOR;
PredictionObstacles prediction_obstacles_;
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/predictor/predictor.h
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define the predictor base class
*/
#pragma once
#include <vector>
#include "modules/prediction/container/adc_trajectory/adc_trajectory_container.h"
#include "modules/prediction/container/obstacles/obstacle.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/common_msgs/prediction_msgs/prediction_obstacle.pb.h"
/**
* @namespace apollo::prediction
* @brief apollo::prediction
*/
namespace apollo {
namespace prediction {
class Predictor {
public:
/**
* @brief Constructor
*/
Predictor() = default;
/**
* @brief Destructor
*/
virtual ~Predictor() = default;
/**
* @brief Make prediction
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
virtual bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) = 0;
/**
* @brief Get trajectory size
* @return Size of trajectories
*/
int NumOfTrajectories(const Obstacle& obstacle);
/**
* @brief Clear all trajectories
*/
virtual void Clear();
/**
* @brief Trim prediction trajectories by adc trajectory
* @param ADC trajectory container
* @param obstacle,
*/
void TrimTrajectories(const ADCTrajectoryContainer& adc_trajectory_container,
Obstacle* obstacle);
/**
* @brief get the predictor type
* @return the predictor type
*/
const ObstacleConf::PredictorType& predictor_type();
protected:
/**
* @brief Generate trajectory from trajectory points
* @param A vector of trajectory points
* @return Generated trajectory
*/
static Trajectory GenerateTrajectory(
const std::vector<apollo::common::TrajectoryPoint>& points);
/**
* @brief Set equal probability to prediction trajectories
* @param probability total probability
* @param start_index The start index to set equal probability
* @param obstacle
*/
void SetEqualProbability(const double probability, const int start_index,
Obstacle* obstacle_ptr);
/**
* @brief Trim a single prediction trajectory,
* keep the portion that is not in junction.
* @param adc_segments trajectory segments of ADC trajectory
* @param obstacle
* @param trajectory The trimed prediction trajectory
* @return If the prediction trajectory is trimed
*/
bool TrimTrajectory(const ADCTrajectoryContainer& adc_trajectory_container,
Obstacle* obstacle, Trajectory* trajectory);
/**
* @brief Determine if an obstacle is supposed to stop within a distance
* @param The latest feature of obstacle
* @param The distance to stop
* @param The output param of acceleration
* @return If the obstacle is supposed to stop within a distance
*/
bool SupposedToStop(const Feature& feature, const double stop_distance,
double* acceleration);
protected:
ObstacleConf::PredictorType predictor_type_;
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/predictor/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "predictor_manager",
srcs = ["predictor_manager.cc"],
hdrs = ["predictor_manager.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/common:feature_output",
"//modules/prediction/common:prediction_thread_pool",
"//modules/prediction/predictor/empty:empty_predictor",
"//modules/prediction/predictor/extrapolation:extrapolation_predictor",
"//modules/prediction/predictor/free_move:free_move_predictor",
"//modules/prediction/predictor/interaction:interaction_predictor",
"//modules/prediction/predictor/junction:junction_predictor",
"//modules/prediction/predictor/lane_sequence:lane_sequence_predictor",
"//modules/prediction/predictor/move_sequence:move_sequence_predictor",
"//modules/prediction/predictor/single_lane:single_lane_predictor",
"//modules/prediction/proto:prediction_conf_cc_proto",
"//modules/prediction/scenario:scenario_manager",
],
)
cc_test(
name = "predictor_manager_test",
size = "small",
srcs = ["predictor_manager_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
linkopts = [
"-lgomp",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/evaluator:evaluator_manager",
"//modules/prediction/predictor:predictor_manager",
],
linkstatic = True,
)
cc_library(
name = "predictor",
srcs = ["predictor.cc"],
hdrs = ["predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/container/adc_trajectory:adc_trajectory_container",
"//modules/prediction/container/obstacles:obstacle",
"//modules/prediction/container/obstacles:obstacles_container",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/predictor/predictor.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/predictor.h"
#include <algorithm>
#include "modules/prediction/common/prediction_gflags.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::TrajectoryPoint;
int Predictor::NumOfTrajectories(const Obstacle& obstacle) {
CHECK_GT(obstacle.history_size(), 0U);
return obstacle.latest_feature().predicted_trajectory_size();
}
Trajectory Predictor::GenerateTrajectory(
const std::vector<TrajectoryPoint>& points) {
Trajectory trajectory;
*trajectory.mutable_trajectory_point() = {points.begin(), points.end()};
return trajectory;
}
void Predictor::SetEqualProbability(const double total_probability,
const int start_index,
Obstacle* obstacle_ptr) {
int num = NumOfTrajectories(*obstacle_ptr);
ACHECK(num > start_index);
const auto prob = total_probability / static_cast<double>(num - start_index);
for (int i = start_index; i < num; ++i) {
obstacle_ptr->mutable_latest_feature()
->mutable_predicted_trajectory(i)
->set_probability(prob);
}
}
void Predictor::Clear() {}
void Predictor::TrimTrajectories(
const ADCTrajectoryContainer& adc_trajectory_container,
Obstacle* obstacle) {
for (auto& predicted_trajectory :
*obstacle->mutable_latest_feature()->mutable_predicted_trajectory()) {
TrimTrajectory(adc_trajectory_container, obstacle, &predicted_trajectory);
}
}
bool Predictor::TrimTrajectory(
const ADCTrajectoryContainer& adc_trajectory_container, Obstacle* obstacle,
Trajectory* trajectory) {
if (!adc_trajectory_container.IsProtected()) {
ADEBUG << "Not in protection mode.";
return false;
}
if (obstacle == nullptr || obstacle->history_size() == 0) {
AERROR << "Invalid obstacle.";
return false;
}
int num_of_point = trajectory->trajectory_point_size();
if (num_of_point == 0) {
return false;
}
const Feature& feature = obstacle->latest_feature();
double vehicle_length = feature.length();
double vehicle_heading = feature.velocity_heading();
double forward_length =
std::fmax(vehicle_length / 2.0 - FLAGS_distance_beyond_junction, 0.0);
double front_x = trajectory->trajectory_point(0).path_point().x() +
forward_length * std::cos(vehicle_heading);
double front_y = trajectory->trajectory_point(0).path_point().y() +
forward_length * std::sin(vehicle_heading);
PathPoint front_point;
front_point.set_x(front_x);
front_point.set_y(front_y);
bool front_in_junction =
adc_trajectory_container.IsPointInJunction(front_point);
const PathPoint& start_point = trajectory->trajectory_point(0).path_point();
bool start_in_junction =
adc_trajectory_container.IsPointInJunction(start_point);
if (front_in_junction || start_in_junction) {
return false;
}
int index = 0;
while (index < num_of_point) {
const PathPoint& point = trajectory->trajectory_point(index).path_point();
if (adc_trajectory_container.IsPointInJunction(point)) {
break;
}
++index;
}
// if no intersect
if (index == num_of_point) {
return false;
}
for (int i = index; i < num_of_point; ++i) {
trajectory->mutable_trajectory_point()->RemoveLast();
}
return true;
}
bool Predictor::SupposedToStop(const Feature& feature,
const double stop_distance,
double* acceleration) {
if (stop_distance < std::max(feature.length() * 0.5, 1.0)) {
return false;
}
if (stop_distance > FLAGS_distance_to_slow_down_at_stop_sign) {
return false;
}
double speed = feature.speed();
*acceleration = -speed * speed / (2.0 * stop_distance);
return *acceleration <= -FLAGS_double_precision &&
*acceleration >= FLAGS_vehicle_min_linear_acc;
}
const ObstacleConf::PredictorType& Predictor::predictor_type() {
return predictor_type_;
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/predictor/predictor_manager.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/predictor_manager.h"
#include <list>
#include <unordered_map>
#include "modules/prediction/common/feature_output.h"
#include "modules/prediction/common/prediction_constants.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/prediction_system_gflags.h"
#include "modules/prediction/common/prediction_thread_pool.h"
#include "modules/prediction/container/container_manager.h"
#include "modules/prediction/predictor/empty/empty_predictor.h"
#include "modules/prediction/predictor/extrapolation/extrapolation_predictor.h"
#include "modules/prediction/predictor/free_move/free_move_predictor.h"
#include "modules/prediction/predictor/interaction/interaction_predictor.h"
#include "modules/prediction/predictor/junction/junction_predictor.h"
#include "modules/prediction/predictor/lane_sequence/lane_sequence_predictor.h"
#include "modules/prediction/predictor/move_sequence/move_sequence_predictor.h"
#include "modules/prediction/predictor/single_lane/single_lane_predictor.h"
#include "modules/prediction/scenario/scenario_manager.h"
namespace apollo {
namespace prediction {
namespace {
using apollo::perception::PerceptionObstacle;
using apollo::perception::PerceptionObstacles;
using IdObstacleListMap = std::unordered_map<int, std::list<Obstacle*>>;
void GroupObstaclesByObstacleId(const int obstacle_id,
ObstaclesContainer* const obstacles_container,
IdObstacleListMap* const id_obstacle_map) {
Obstacle* obstacle_ptr = obstacles_container->GetObstacle(obstacle_id);
if (obstacle_ptr == nullptr) {
AERROR << "Null obstacle [" << obstacle_id << "] found";
return;
}
int id_mod = obstacle_id % FLAGS_max_thread_num;
(*id_obstacle_map)[id_mod].push_back(obstacle_ptr);
}
} // namespace
PredictorManager::PredictorManager() { RegisterPredictors(); }
void PredictorManager::RegisterPredictors() {
RegisterPredictor(ObstacleConf::LANE_SEQUENCE_PREDICTOR);
RegisterPredictor(ObstacleConf::MOVE_SEQUENCE_PREDICTOR);
RegisterPredictor(ObstacleConf::SINGLE_LANE_PREDICTOR);
RegisterPredictor(ObstacleConf::FREE_MOVE_PREDICTOR);
RegisterPredictor(ObstacleConf::EMPTY_PREDICTOR);
RegisterPredictor(ObstacleConf::JUNCTION_PREDICTOR);
RegisterPredictor(ObstacleConf::EXTRAPOLATION_PREDICTOR);
RegisterPredictor(ObstacleConf::INTERACTION_PREDICTOR);
}
void PredictorManager::Init(const PredictionConf& config) {
for (const auto& conf : config.obstacle_conf()) {
if (!conf.has_obstacle_type()) {
AERROR << "Obstacle config [" << conf.ShortDebugString()
<< "] has not defined obstacle type.";
continue;
}
if (!conf.has_predictor_type()) {
AERROR << "Obstacle config [" << conf.ShortDebugString()
<< "] has not defined predictor type.";
continue;
}
switch (conf.obstacle_type()) {
case PerceptionObstacle::VEHICLE: {
InitVehiclePredictors(conf);
break;
}
case PerceptionObstacle::BICYCLE: {
InitCyclistPredictors(conf);
break;
}
case PerceptionObstacle::PEDESTRIAN: {
pedestrian_predictor_ = conf.predictor_type();
break;
}
case PerceptionObstacle::UNKNOWN: {
InitDefaultPredictors(conf);
break;
}
default: { break; }
}
}
AINFO << "Defined vehicle on lane obstacle predictor ["
<< vehicle_on_lane_predictor_ << "].";
AINFO << "Defined vehicle off lane obstacle predictor ["
<< vehicle_off_lane_predictor_ << "].";
AINFO << "Defined bicycle on lane obstacle predictor ["
<< cyclist_on_lane_predictor_ << "].";
AINFO << "Defined bicycle off lane obstacle predictor ["
<< cyclist_off_lane_predictor_ << "].";
AINFO << "Defined pedestrian obstacle predictor [" << pedestrian_predictor_
<< "].";
AINFO << "Defined default on lane obstacle predictor ["
<< default_on_lane_predictor_ << "].";
AINFO << "Defined default off lane obstacle predictor ["
<< default_off_lane_predictor_ << "].";
}
Predictor* PredictorManager::GetPredictor(
const ObstacleConf::PredictorType& type) {
auto it = predictors_.find(type);
return it != predictors_.end() ? it->second.get() : nullptr;
}
void PredictorManager::Run(
const PerceptionObstacles& perception_obstacles,
const ADCTrajectoryContainer* adc_trajectory_container,
ObstaclesContainer* obstacles_container) {
prediction_obstacles_.Clear();
if (FLAGS_enable_multi_thread) {
PredictObstaclesInParallel(perception_obstacles, adc_trajectory_container,
obstacles_container);
} else {
PredictObstacles(perception_obstacles, adc_trajectory_container,
obstacles_container);
}
}
void PredictorManager::PredictObstacles(
const PerceptionObstacles& perception_obstacles,
const ADCTrajectoryContainer* adc_trajectory_container,
ObstaclesContainer* obstacles_container) {
for (const PerceptionObstacle& perception_obstacle :
perception_obstacles.perception_obstacle()) {
int id = perception_obstacle.id();
if (id < 0) {
ADEBUG << "The obstacle has invalid id [" << id << "].";
continue;
}
PredictionObstacle prediction_obstacle;
Obstacle* obstacle = obstacles_container->GetObstacle(id);
// if obstacle == nullptr, that means obstacle is unmovable
// Checkout the logic of unmovable in obstacle.cc
if (obstacle != nullptr) {
PredictObstacle(adc_trajectory_container, obstacle, obstacles_container,
&prediction_obstacle);
} else { // obstacle == nullptr
prediction_obstacle.set_timestamp(perception_obstacle.timestamp());
prediction_obstacle.set_is_static(true);
}
prediction_obstacle.set_predicted_period(
FLAGS_prediction_trajectory_time_length);
prediction_obstacle.mutable_perception_obstacle()->CopyFrom(
perception_obstacle);
prediction_obstacles_.add_prediction_obstacle()->CopyFrom(
prediction_obstacle);
}
}
void PredictorManager::PredictObstaclesInParallel(
const PerceptionObstacles& perception_obstacles,
const ADCTrajectoryContainer* adc_trajectory_container,
ObstaclesContainer* obstacles_container) {
std::unordered_map<int, std::shared_ptr<PredictionObstacle>>
id_prediction_obstacle_map;
for (const PerceptionObstacle& perception_obstacle :
perception_obstacles.perception_obstacle()) {
int id = perception_obstacle.id();
id_prediction_obstacle_map[id] = std::make_shared<PredictionObstacle>();
}
IdObstacleListMap id_obstacle_map;
for (const auto& perception_obstacle :
perception_obstacles.perception_obstacle()) {
int id = perception_obstacle.id();
Obstacle* obstacle = obstacles_container->GetObstacle(id);
if (obstacle == nullptr) {
std::shared_ptr<PredictionObstacle> prediction_obstacle_ptr =
id_prediction_obstacle_map[id];
prediction_obstacle_ptr->set_is_static(true);
prediction_obstacle_ptr->set_timestamp(perception_obstacle.timestamp());
} else {
GroupObstaclesByObstacleId(id, obstacles_container, &id_obstacle_map);
}
}
PredictionThreadPool::ForEach(
id_obstacle_map.begin(), id_obstacle_map.end(),
[&](IdObstacleListMap::iterator::value_type& obstacles_iter) {
for (auto obstacle_ptr : obstacles_iter.second) {
int id = obstacle_ptr->id();
PredictObstacle(adc_trajectory_container, obstacle_ptr,
obstacles_container,
id_prediction_obstacle_map[id].get());
}
});
for (const PerceptionObstacle& perception_obstacle :
perception_obstacles.perception_obstacle()) {
int id = perception_obstacle.id();
auto prediction_obstacle_ptr = id_prediction_obstacle_map[id];
if (prediction_obstacle_ptr == nullptr) {
AERROR << "Prediction obstacle [" << id << "] not found.";
continue;
}
prediction_obstacle_ptr->set_predicted_period(
FLAGS_prediction_trajectory_time_length);
prediction_obstacle_ptr->mutable_perception_obstacle()->CopyFrom(
perception_obstacle);
prediction_obstacles_.add_prediction_obstacle()->CopyFrom(
*prediction_obstacle_ptr);
}
}
void PredictorManager::PredictObstacle(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container,
PredictionObstacle* const prediction_obstacle) {
CHECK_NOTNULL(obstacle);
prediction_obstacle->set_timestamp(obstacle->timestamp());
if (obstacle->ToIgnore()) {
ADEBUG << "Ignore obstacle [" << obstacle->id() << "]";
RunEmptyPredictor(adc_trajectory_container, obstacle, obstacles_container);
prediction_obstacle->mutable_priority()->set_priority(
ObstaclePriority::IGNORE);
} else if (obstacle->IsStill()) {
ADEBUG << "Still obstacle [" << obstacle->id() << "]";
RunEmptyPredictor(adc_trajectory_container, obstacle, obstacles_container);
} else {
switch (obstacle->type()) {
case PerceptionObstacle::VEHICLE: {
RunVehiclePredictor(adc_trajectory_container, obstacle,
obstacles_container);
break;
}
case PerceptionObstacle::PEDESTRIAN: {
RunPedestrianPredictor(adc_trajectory_container, obstacle,
obstacles_container);
break;
}
case PerceptionObstacle::BICYCLE: {
RunCyclistPredictor(adc_trajectory_container, obstacle,
obstacles_container);
break;
}
default: {
RunDefaultPredictor(adc_trajectory_container, obstacle,
obstacles_container);
break;
}
}
}
for (const auto& trajectory :
obstacle->latest_feature().predicted_trajectory()) {
prediction_obstacle->add_trajectory()->CopyFrom(trajectory);
}
prediction_obstacle->set_timestamp(obstacle->timestamp());
prediction_obstacle->mutable_priority()->CopyFrom(
obstacle->latest_feature().priority());
prediction_obstacle->mutable_interactive_tag()->CopyFrom(
obstacle->latest_feature().interactive_tag());
prediction_obstacle->set_is_static(obstacle->IsStill());
if (FLAGS_prediction_offline_mode ==
PredictionConstants::kDumpPredictionResult) {
const Scenario& scenario = obstacles_container->curr_scenario();
FeatureOutput::InsertPredictionResult(obstacle, *prediction_obstacle,
obstacle->obstacle_conf(), scenario);
}
}
std::unique_ptr<Predictor> PredictorManager::CreatePredictor(
const ObstacleConf::PredictorType& type) {
std::unique_ptr<Predictor> predictor_ptr(nullptr);
switch (type) {
case ObstacleConf::LANE_SEQUENCE_PREDICTOR: {
predictor_ptr.reset(new LaneSequencePredictor());
break;
}
case ObstacleConf::MOVE_SEQUENCE_PREDICTOR: {
predictor_ptr.reset(new MoveSequencePredictor());
break;
}
case ObstacleConf::SINGLE_LANE_PREDICTOR: {
predictor_ptr.reset(new SingleLanePredictor());
break;
}
case ObstacleConf::FREE_MOVE_PREDICTOR: {
predictor_ptr.reset(new FreeMovePredictor());
break;
}
case ObstacleConf::JUNCTION_PREDICTOR: {
predictor_ptr.reset(new JunctionPredictor());
break;
}
case ObstacleConf::EXTRAPOLATION_PREDICTOR: {
predictor_ptr.reset(new ExtrapolationPredictor());
break;
}
case ObstacleConf::INTERACTION_PREDICTOR: {
predictor_ptr.reset(new InteractionPredictor());
break;
}
case ObstacleConf::EMPTY_PREDICTOR: {
predictor_ptr.reset(new EmptyPredictor());
break;
}
default: { break; }
}
return predictor_ptr;
}
void PredictorManager::RegisterPredictor(
const ObstacleConf::PredictorType& type) {
predictors_[type] = CreatePredictor(type);
AINFO << "Predictor [" << type << "] is registered.";
}
const PredictionObstacles& PredictorManager::prediction_obstacles() {
return prediction_obstacles_;
}
void PredictorManager::InitVehiclePredictors(const ObstacleConf& conf) {
if (!conf.has_obstacle_status() && conf.has_interactive_tag()) {
vehicle_interactive_predictor_ = conf.predictor_type();
}
switch (conf.obstacle_status()) {
case ObstacleConf::ON_LANE: {
if (conf.priority_type() == ObstaclePriority::CAUTION) {
vehicle_on_lane_caution_predictor_ = conf.predictor_type();
} else {
vehicle_on_lane_predictor_ = conf.predictor_type();
}
break;
}
case ObstacleConf::OFF_LANE: {
vehicle_off_lane_predictor_ = conf.predictor_type();
break;
}
case ObstacleConf::IN_JUNCTION: {
if (conf.priority_type() == ObstaclePriority::CAUTION) {
vehicle_in_junction_caution_predictor_ = conf.predictor_type();
} else {
vehicle_in_junction_predictor_ = conf.predictor_type();
}
break;
}
default: { break; }
}
}
void PredictorManager::InitCyclistPredictors(const ObstacleConf& conf) {
switch (conf.obstacle_status()) {
case ObstacleConf::ON_LANE: {
cyclist_on_lane_predictor_ = conf.predictor_type();
break;
}
case ObstacleConf::OFF_LANE: {
cyclist_off_lane_predictor_ = conf.predictor_type();
break;
}
default: { break; }
}
}
void PredictorManager::InitDefaultPredictors(const ObstacleConf& conf) {
switch (conf.obstacle_status()) {
case ObstacleConf::ON_LANE: {
default_on_lane_predictor_ = conf.predictor_type();
break;
}
case ObstacleConf::OFF_LANE: {
default_off_lane_predictor_ = conf.predictor_type();
break;
}
default: { break; }
}
}
void PredictorManager::RunVehiclePredictor(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Predictor* predictor = nullptr;
if (obstacle->IsInteractiveObstacle()) {
predictor = GetPredictor(vehicle_interactive_predictor_);
if (predictor->Predict(adc_trajectory_container, obstacle,
obstacles_container)) {
return;
} else {
AERROR << "Obstacle: " << obstacle->id()
<< " interactive predictor failed!";
}
}
if (obstacle->IsCaution()) {
if (obstacle->IsNearJunction()) {
predictor = GetPredictor(vehicle_in_junction_caution_predictor_);
} else if (obstacle->IsOnLane()) {
predictor = GetPredictor(vehicle_on_lane_caution_predictor_);
} else {
predictor = GetPredictor(vehicle_default_caution_predictor_);
}
CHECK_NOTNULL(predictor);
if (predictor->Predict(adc_trajectory_container, obstacle,
obstacles_container)) {
return;
} else {
AERROR << "Obstacle: " << obstacle->id()
<< " caution predictor failed, downgrade to normal level!";
}
}
if (!obstacle->IsOnLane()) {
predictor = GetPredictor(vehicle_off_lane_predictor_);
} else if (obstacle->HasJunctionFeatureWithExits() &&
!obstacle->IsCloseToJunctionExit()) {
predictor = GetPredictor(vehicle_in_junction_predictor_);
} else {
predictor = GetPredictor(vehicle_on_lane_predictor_);
}
if (predictor == nullptr) {
AERROR << "Nullptr found for obstacle [" << obstacle->id() << "]";
return;
}
predictor->Predict(adc_trajectory_container, obstacle, obstacles_container);
if (FLAGS_enable_trim_prediction_trajectory) {
CHECK_NOTNULL(adc_trajectory_container);
predictor->TrimTrajectories(*adc_trajectory_container, obstacle);
}
}
void PredictorManager::RunPedestrianPredictor(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Predictor* predictor = nullptr;
predictor = GetPredictor(pedestrian_predictor_);
if (predictor == nullptr) {
AERROR << "Nullptr found for obstacle [" << obstacle->id() << "]";
return;
}
predictor->Predict(adc_trajectory_container, obstacle, obstacles_container);
}
void PredictorManager::RunCyclistPredictor(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Predictor* predictor = nullptr;
if (obstacle->IsOnLane()) {
predictor = GetPredictor(cyclist_on_lane_predictor_);
} else {
predictor = GetPredictor(cyclist_off_lane_predictor_);
}
if (predictor == nullptr) {
AERROR << "Nullptr found for obstacle [" << obstacle->id() << "]";
return;
}
predictor->Predict(adc_trajectory_container, obstacle, obstacles_container);
}
void PredictorManager::RunDefaultPredictor(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Predictor* predictor = nullptr;
if (obstacle->IsOnLane()) {
predictor = GetPredictor(default_on_lane_predictor_);
} else {
predictor = GetPredictor(default_off_lane_predictor_);
}
if (predictor == nullptr) {
AERROR << "Nullptr found for obstacle [" << obstacle->id() << "]";
return;
}
predictor->Predict(adc_trajectory_container, obstacle, obstacles_container);
}
void PredictorManager::RunEmptyPredictor(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Predictor* predictor = GetPredictor(ObstacleConf::EMPTY_PREDICTOR);
if (predictor == nullptr) {
AERROR << "Nullptr found for obstacle [" << obstacle->id() << "]";
return;
}
predictor->Predict(adc_trajectory_container, obstacle, obstacles_container);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/single_lane/single_lane_predictor.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
*implied. See the License for the specific language governing
*permissions and limitations under the License.
*****************************************************************************/
/**
* @file
*/
#pragma once
#include <vector>
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
namespace apollo {
namespace prediction {
class SingleLanePredictor : public SequencePredictor {
public:
/**
* @brief Constructor
*/
SingleLanePredictor();
/**
* @brief Destructor
*/
virtual ~SingleLanePredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
protected:
/**
* @brief Draw lane sequence trajectory points
* @param Obstacle
* @param Lane sequence
* @param Total prediction time
* @param Prediction period
* @param A vector of generated trajectory points
*/
void GenerateTrajectoryPoints(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period,
std::vector<apollo::common::TrajectoryPoint>* points);
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/single_lane/single_lane_predictor.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
*implied. See the License for the specific language governing
*permissions and limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/single_lane/single_lane_predictor.h"
#include <memory>
#include <string>
#include <utility>
#include "modules/prediction/common/prediction_gflags.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::TrajectoryPoint;
using apollo::hdmap::LaneInfo;
SingleLanePredictor::SingleLanePredictor() {
predictor_type_ = ObstacleConf::SINGLE_LANE_PREDICTOR;
}
bool SingleLanePredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
obstacle->SetPredictorType(predictor_type_);
const Feature& feature = obstacle->latest_feature();
if (!feature.has_lane() || !feature.lane().has_lane_graph()) {
AERROR << "Obstacle [" << obstacle->id() << "] has no lane graph.";
return false;
}
std::string lane_id = "";
if (feature.lane().has_lane_feature()) {
lane_id = feature.lane().lane_feature().lane_id();
}
int num_lane_sequence = feature.lane().lane_graph().lane_sequence_size();
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& sequence = feature.lane().lane_graph().lane_sequence(i);
if (sequence.lane_segment().empty()) {
AERROR << "Empty lane segments.";
continue;
}
ADEBUG << "Obstacle [" << obstacle->id()
<< "] will draw a lane sequence trajectory [" << ToString(sequence)
<< "] with probability [" << sequence.probability() << "].";
std::vector<TrajectoryPoint> points;
GenerateTrajectoryPoints(
*obstacle, sequence, FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, &points);
if (points.empty()) {
continue;
}
Trajectory trajectory = GenerateTrajectory(points);
trajectory.set_probability(sequence.probability());
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
}
return true;
}
void SingleLanePredictor::GenerateTrajectoryPoints(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double time_length, const double time_resolution,
std::vector<TrajectoryPoint>* points) {
const Feature& feature = obstacle.latest_feature();
if (!feature.has_position() || !feature.has_velocity() ||
!feature.position().has_x() || !feature.position().has_y()) {
AERROR << "Obstacle [" << obstacle.id()
<< " is missing position or velocity";
return;
}
double probability = lane_sequence.probability();
double approach_rate = FLAGS_go_approach_rate;
if (probability < FLAGS_lane_sequence_threshold_cruise) {
approach_rate = 1.0;
}
Eigen::Vector2d position(feature.position().x(), feature.position().y());
double speed = feature.speed();
int lane_segment_index = 0;
std::string lane_id =
lane_sequence.lane_segment(lane_segment_index).lane_id();
std::shared_ptr<const LaneInfo> lane_info = PredictionMap::LaneById(lane_id);
double lane_s = 0.0;
double lane_l = 0.0;
if (!PredictionMap::GetProjection(position, lane_info, &lane_s, &lane_l)) {
AERROR << "Failed in getting lane s and lane l";
return;
}
size_t num_of_points = static_cast<size_t>(time_length / time_resolution);
for (size_t i = 0; i < num_of_points; ++i) {
double relative_time = static_cast<double>(i) * time_resolution;
Eigen::Vector2d point;
double theta = M_PI;
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, lane_l, &point,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << lane_l << "]";
break;
}
TrajectoryPoint trajectory_point;
PathPoint path_point;
path_point.set_x(point.x());
path_point.set_y(point.y());
path_point.set_z(0.0);
path_point.set_theta(theta);
path_point.set_lane_id(lane_id);
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(speed);
trajectory_point.set_a(0.0);
trajectory_point.set_relative_time(relative_time);
points->emplace_back(std::move(trajectory_point));
lane_s += speed * time_resolution;
while (lane_s > PredictionMap::LaneById(lane_id)->total_length() &&
lane_segment_index + 1 < lane_sequence.lane_segment_size()) {
lane_segment_index += 1;
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
lane_id = lane_sequence.lane_segment(lane_segment_index).lane_id();
}
lane_l *= approach_rate;
}
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/single_lane/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "single_lane_predictor",
srcs = ["single_lane_predictor.cc"],
hdrs = ["single_lane_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/predictor/sequence:sequence_predictor",
],
)
cc_test(
name = "single_lane_predictor_test",
size = "small",
srcs = ["single_lane_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/evaluator/vehicle:cost_evaluator",
"//modules/prediction/predictor/single_lane:single_lane_predictor",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/single_lane/single_lane_predictor_test.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/single_lane/single_lane_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/cost_evaluator.h"
namespace apollo {
namespace prediction {
class SingleLanePredictorTest : public KMLMapBasedTest {
public:
virtual void SetUp() {
const std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
cyber::common::GetProtoFromFile(file, &perception_obstacles_);
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(SingleLanePredictorTest, OnLaneCase) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
CostEvaluator cost_evaluator;
ObstaclesContainer container;
container.Insert(perception_obstacles_);
container.BuildLaneGraph();
ADCTrajectoryContainer adc_trajectory_container;
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
cost_evaluator.Evaluate(obstacle_ptr, &container);
SingleLanePredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 2);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/empty/empty_predictor.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
*/
#pragma once
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/predictor/predictor.h"
namespace apollo {
namespace prediction {
class EmptyPredictor : public Predictor {
public:
/**
* @brief Constructor
*/
EmptyPredictor();
/**
* @brief Destructor
*/
virtual ~EmptyPredictor() = default;
/**
* @brief Make prediction
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/empty/empty_predictor_test.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/empty/empty_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/mlp_evaluator.h"
namespace apollo {
namespace prediction {
class EmptyPredictorTest : public KMLMapBasedTest {
public:
virtual void SetUp() {
const std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
cyber::common::GetProtoFromFile(file, &perception_obstacles_);
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(EmptyPredictorTest, General) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator evaluator;
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
evaluator.Evaluate(obstacle_ptr, &container);
EmptyPredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 0);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/empty/empty_predictor.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/empty/empty_predictor.h"
namespace apollo {
namespace prediction {
EmptyPredictor::EmptyPredictor() {
predictor_type_ = ObstacleConf::EMPTY_PREDICTOR;
}
bool EmptyPredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
obstacle->SetPredictorType(predictor_type_);
return true;
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/empty/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "empty_predictor",
srcs = ["empty_predictor.cc"],
hdrs = ["empty_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/predictor",
],
)
cc_test(
name = "empty_predictor_test",
size = "small",
srcs = ["empty_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/container/obstacles:obstacles_container",
"//modules/prediction/evaluator/vehicle:mlp_evaluator",
"//modules/prediction/predictor/empty:empty_predictor",
"@com_google_googletest//:gtest_main",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/lane_sequence/lane_sequence_predictor.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/lane_sequence/lane_sequence_predictor.h"
#include <memory>
#include <string>
#include <utility>
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/validation_checker.h"
#include "modules/prediction/proto/prediction_conf.pb.h"
namespace apollo {
namespace prediction {
using common::PathPoint;
using common::TrajectoryPoint;
using hdmap::LaneInfo;
LaneSequencePredictor::LaneSequencePredictor() {
predictor_type_ = ObstacleConf::LANE_SEQUENCE_PREDICTOR;
}
bool LaneSequencePredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
obstacle->SetPredictorType(predictor_type_);
const Feature& feature = obstacle->latest_feature();
if (!feature.has_lane() || !feature.lane().has_lane_graph()) {
AERROR << "Obstacle [" << obstacle->id() << " has no lane graph.";
return false;
}
std::string lane_id = "";
if (feature.lane().has_lane_feature()) {
lane_id = feature.lane().lane_feature().lane_id();
}
int num_lane_sequence = feature.lane().lane_graph().lane_sequence_size();
std::vector<bool> enable_lane_sequence(num_lane_sequence, true);
Obstacle* ego_vehicle_ptr =
obstacles_container->GetObstacle(FLAGS_ego_vehicle_id);
FilterLaneSequences(feature, lane_id, ego_vehicle_ptr,
adc_trajectory_container, &enable_lane_sequence);
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& sequence = feature.lane().lane_graph().lane_sequence(i);
if (sequence.lane_segment().empty()) {
AERROR << "Empty lane segments.";
continue;
}
if (!enable_lane_sequence[i]) {
ADEBUG << "Lane sequence [" << ToString(sequence)
<< "] with probability [" << sequence.probability()
<< "] is disqualified.";
continue;
}
ADEBUG << "Obstacle [" << obstacle->id()
<< "] will draw a lane sequence trajectory [" << ToString(sequence)
<< "] with probability [" << sequence.probability() << "].";
std::vector<TrajectoryPoint> points;
bool is_about_to_stop = false;
double acceleration = 0.0;
if (sequence.has_stop_sign()) {
double stop_distance =
sequence.stop_sign().lane_sequence_s() - sequence.lane_s();
is_about_to_stop = SupposedToStop(feature, stop_distance, &acceleration);
}
if (is_about_to_stop) {
DrawConstantAccelerationTrajectory(
*obstacle, sequence, FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, acceleration, &points);
} else {
DrawLaneSequenceTrajectoryPoints(
*obstacle, sequence, FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, &points);
}
if (points.empty()) {
continue;
}
if (FLAGS_enable_trajectory_validation_check &&
!ValidationChecker::ValidCentripetalAcceleration(points)) {
continue;
}
Trajectory trajectory = GenerateTrajectory(points);
trajectory.set_probability(sequence.probability());
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
}
return true;
}
void LaneSequencePredictor::DrawLaneSequenceTrajectoryPoints(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period,
std::vector<TrajectoryPoint>* points) {
const Feature& feature = obstacle.latest_feature();
if (!feature.has_position() || !feature.has_velocity() ||
!feature.position().has_x() || !feature.position().has_y()) {
AERROR << "Obstacle [" << obstacle.id()
<< " is missing position or velocity";
return;
}
Eigen::Vector2d position(feature.position().x(), feature.position().y());
double speed = feature.speed();
int lane_segment_index = 0;
std::string lane_id =
lane_sequence.lane_segment(lane_segment_index).lane_id();
std::shared_ptr<const LaneInfo> lane_info = PredictionMap::LaneById(lane_id);
double lane_s = 0.0;
double lane_l = 0.0;
if (!PredictionMap::GetProjection(position, lane_info, &lane_s, &lane_l)) {
AERROR << "Failed in getting lane s and lane l";
return;
}
double approach_rate = FLAGS_go_approach_rate;
if (!lane_sequence.vehicle_on_lane()) {
approach_rate = FLAGS_cutin_approach_rate;
}
size_t total_num = static_cast<size_t>(total_time / period);
for (size_t i = 0; i < total_num; ++i) {
double relative_time = static_cast<double>(i) * period;
Eigen::Vector2d point;
double theta = M_PI;
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, lane_l, &point,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << lane_l << "]";
break;
}
TrajectoryPoint trajectory_point;
PathPoint path_point;
path_point.set_x(point.x());
path_point.set_y(point.y());
path_point.set_z(0.0);
path_point.set_theta(theta);
path_point.set_lane_id(lane_id);
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(speed);
trajectory_point.set_a(0.0);
trajectory_point.set_relative_time(relative_time);
points->emplace_back(std::move(trajectory_point));
lane_s += speed * period;
while (lane_s > PredictionMap::LaneById(lane_id)->total_length() &&
lane_segment_index + 1 < lane_sequence.lane_segment_size()) {
lane_segment_index += 1;
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
lane_id = lane_sequence.lane_segment(lane_segment_index).lane_id();
}
lane_l *= approach_rate;
}
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/lane_sequence/lane_sequence_predictor_test.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/lane_sequence/lane_sequence_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/mlp_evaluator.h"
namespace apollo {
namespace prediction {
class LaneSequencePredictorTest : public KMLMapBasedTest {
public:
virtual void SetUp() {
std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
cyber::common::GetProtoFromFile(file, &perception_obstacles_);
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(LaneSequencePredictorTest, OnLaneCase) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator mlp_evaluator;
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
container.BuildLaneGraph();
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
mlp_evaluator.Evaluate(obstacle_ptr, &container);
LaneSequencePredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 1);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/lane_sequence/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "lane_sequence_predictor",
srcs = ["lane_sequence_predictor.cc"],
hdrs = ["lane_sequence_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/common:validation_checker",
"//modules/prediction/predictor/sequence:sequence_predictor",
],
)
cc_test(
name = "lane_sequence_predictor_test",
size = "small",
srcs = ["lane_sequence_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/evaluator/vehicle:mlp_evaluator",
"//modules/prediction/predictor/lane_sequence:lane_sequence_predictor",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/lane_sequence/lane_sequence_predictor.h
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
*implied. See the License for the specific language governing
*permissions and limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define lane sequence predictor
*/
#pragma once
#include <vector>
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
namespace apollo {
namespace prediction {
class LaneSequencePredictor : public SequencePredictor {
public:
/**
* @brief Constructor
*/
LaneSequencePredictor();
/**
* @brief Destructor
*/
virtual ~LaneSequencePredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
protected:
/**
* @brief Draw lane sequence trajectory points
* @param Obstacle
* @param Lane sequence
* @param Total prediction time
* @param Prediction period
* @param A vector of generated trajectory points
*/
void DrawLaneSequenceTrajectoryPoints(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period,
std::vector<apollo::common::TrajectoryPoint>* points);
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/move_sequence/move_sequence_predictor.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/move_sequence/move_sequence_predictor.h"
#include <algorithm>
#include <memory>
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/prediction_util.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::TrajectoryPoint;
using apollo::hdmap::LaneInfo;
using apollo::prediction::math_util::EvaluateCubicPolynomial;
using apollo::prediction::math_util::EvaluateQuarticPolynomial;
MoveSequencePredictor::MoveSequencePredictor() {
predictor_type_ = ObstacleConf::MOVE_SEQUENCE_PREDICTOR;
}
bool MoveSequencePredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
obstacle->SetPredictorType(predictor_type_);
const Feature& feature = obstacle->latest_feature();
if (!feature.has_lane() || !feature.lane().has_lane_graph()) {
AERROR << "Obstacle [" << obstacle->id() << "] has no lane graph.";
return false;
}
std::string lane_id = "";
if (feature.lane().has_lane_feature()) {
lane_id = feature.lane().lane_feature().lane_id();
}
int num_lane_sequence = feature.lane().lane_graph().lane_sequence_size();
std::vector<bool> enable_lane_sequence(num_lane_sequence, true);
Obstacle* ego_vehicle_ptr =
obstacles_container->GetObstacle(FLAGS_ego_vehicle_id);
FilterLaneSequences(feature, lane_id, ego_vehicle_ptr,
adc_trajectory_container, &enable_lane_sequence);
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& sequence = feature.lane().lane_graph().lane_sequence(i);
if (sequence.lane_segment().empty() ||
sequence.lane_segment(0).lane_point().empty()) {
ADEBUG << "Empty lane segments.";
continue;
}
if (!enable_lane_sequence[i]) {
ADEBUG << "Lane sequence [" << ToString(sequence)
<< "] with probability [" << sequence.probability()
<< "] is disqualified.";
continue;
}
ADEBUG << "Obstacle [" << obstacle->id()
<< "] will draw a lane sequence trajectory [" << ToString(sequence)
<< "] with probability [" << sequence.probability() << "].";
std::vector<TrajectoryPoint> points;
auto end_time1 = std::chrono::system_clock::now();
bool is_about_to_stop = false;
double acceleration = 0.0;
if (sequence.has_stop_sign()) {
double stop_distance =
sequence.stop_sign().lane_sequence_s() - sequence.lane_s();
is_about_to_stop = SupposedToStop(feature, stop_distance, &acceleration);
}
if (is_about_to_stop) {
DrawConstantAccelerationTrajectory(
*obstacle, sequence, FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, acceleration, &points);
} else {
DrawMoveSequenceTrajectoryPoints(
*obstacle, sequence, FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, &points);
}
auto end_time2 = std::chrono::system_clock::now();
std::chrono::duration<double> diff = end_time2 - end_time1;
ADEBUG << " Time to draw trajectory: " << diff.count() * 1000 << " msec.";
Trajectory trajectory = GenerateTrajectory(points);
trajectory.set_probability(sequence.probability());
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
}
return true;
}
/**
* For this function:
* Input: obstacle status, lane-sequence, the total time of prediction,
* and the time interval between two adjacent points when plotting.
* Output: A vector of TrajectoryPoint
*/
bool MoveSequencePredictor::DrawMoveSequenceTrajectoryPoints(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period,
std::vector<TrajectoryPoint>* points) {
// Sanity check.
points->clear();
CHECK_NOTNULL(points);
const Feature& feature = obstacle.latest_feature();
if (!feature.has_position() || !feature.has_velocity() ||
!feature.position().has_x() || !feature.position().has_y()) {
AERROR << "Obstacle [" << obstacle.id()
<< " is missing position or velocity";
return false;
}
// Fit the lateral and longitudinal polynomials.
Eigen::Vector2d position(feature.position().x(), feature.position().y());
double time_to_lat_end_state =
std::max(FLAGS_default_time_to_lat_end_state,
ComputeTimeToLatEndConditionByVelocity(obstacle, lane_sequence));
double vel_heading = feature.velocity_heading();
double feature_v = feature.speed();
double feature_a = 0.0;
if (FLAGS_enable_lane_sequence_acc && lane_sequence.has_acceleration()) {
feature_a = lane_sequence.acceleration();
}
double lane_heading = lane_sequence.lane_segment(0).lane_point(0).heading();
double s0 = 0.0;
double ds0 = feature_v * std::cos(vel_heading - lane_heading);
double dds0 = feature_a * std::cos(vel_heading - lane_heading);
std::pair<double, double> lon_end_vt =
ComputeLonEndState({s0, ds0, dds0}, lane_sequence);
std::array<double, 4> lateral_coeffs;
std::array<double, 5> longitudinal_coeffs;
GetLateralPolynomial(obstacle, lane_sequence, time_to_lat_end_state,
&lateral_coeffs);
GetLongitudinalPolynomial(obstacle, lane_sequence, lon_end_vt,
&longitudinal_coeffs);
// Get ready for the for-loop:
// project the obstacle's position onto the lane's Frenet coordinates.
int lane_segment_index = lane_sequence.adc_lane_segment_idx();
std::string lane_id =
lane_sequence.lane_segment(lane_segment_index).lane_id();
std::shared_ptr<const LaneInfo> lane_info = PredictionMap::LaneById(lane_id);
double lane_s = 0.0;
double lane_l = 0.0;
if (!PredictionMap::GetProjection(position, lane_info, &lane_s, &lane_l)) {
AERROR << "Failed in getting lane s and lane l";
return false;
}
double prev_lane_l = lane_l;
// Draw each trajectory point within the total time of prediction
size_t total_num = static_cast<size_t>(total_time / period);
for (size_t i = 0; i < total_num; ++i) {
double relative_time = static_cast<double>(i) * period;
Eigen::Vector2d point;
double theta = M_PI;
lane_l = EvaluateCubicPolynomial(lateral_coeffs, relative_time, 0,
time_to_lat_end_state, 0.0);
double curr_s =
EvaluateQuarticPolynomial(longitudinal_coeffs, relative_time, 0,
lon_end_vt.second, lon_end_vt.first);
double prev_s = (i > 0) ? EvaluateQuarticPolynomial(
longitudinal_coeffs, relative_time - period,
0, lon_end_vt.second, lon_end_vt.first)
: 0.0;
lane_s += std::max(0.0, (curr_s - prev_s));
if (curr_s + FLAGS_double_precision < prev_s) {
lane_l = prev_lane_l;
}
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, lane_l, &point,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << lane_l << "]";
break;
}
prev_lane_l = lane_l;
double lane_speed =
EvaluateQuarticPolynomial(longitudinal_coeffs, relative_time, 1,
lon_end_vt.second, lon_end_vt.first);
double lane_acc =
EvaluateQuarticPolynomial(longitudinal_coeffs, relative_time, 2,
lon_end_vt.second, lon_end_vt.first);
TrajectoryPoint trajectory_point;
PathPoint path_point;
path_point.set_x(point.x());
path_point.set_y(point.y());
path_point.set_z(0.0);
path_point.set_theta(theta);
path_point.set_lane_id(lane_id);
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(lane_speed);
trajectory_point.set_a(lane_acc);
trajectory_point.set_relative_time(relative_time);
points->emplace_back(std::move(trajectory_point));
while (lane_s > PredictionMap::LaneById(lane_id)->total_length() &&
lane_segment_index + 1 < lane_sequence.lane_segment_size()) {
lane_segment_index += 1;
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
lane_id = lane_sequence.lane_segment(lane_segment_index).lane_id();
}
}
return true;
}
std::pair<double, double> MoveSequencePredictor::ComputeLonEndState(
const std::array<double, 3>& init_s, const LaneSequence& lane_sequence) {
// Get the maximum kappa of the lane.
double max_kappa = 0.0;
double s_at_max_kappa = 0.0;
for (int i = 0; i < lane_sequence.path_point_size(); ++i) {
const PathPoint& path_point = lane_sequence.path_point(i);
if (path_point.s() < init_s[0] + FLAGS_double_precision) {
continue;
}
if (max_kappa < path_point.kappa()) {
max_kappa = path_point.kappa();
s_at_max_kappa = path_point.s();
}
}
// If the max. curvature is small (almost straight lane),
// then predict that the obstacle will keep current speed.
double v_init = init_s[1];
if (max_kappa < FLAGS_turning_curvature_lower_bound) {
return {v_init, FLAGS_prediction_trajectory_time_length};
}
// (Calculate the speed at the max. curvature point)
double v_end = apollo::prediction::predictor_util::AdjustSpeedByCurvature(
init_s[1], max_kappa);
// If the calculated speed at max. curvature point is higher
// than initial speed, don't accelerate, just predict that
// the obstacle will maintain current speed.
if (v_end + FLAGS_double_precision > v_init) {
return {v_init, FLAGS_prediction_trajectory_time_length};
}
// If the obstacle is already at the max. curvature point,
// then predict that it will maintain the current speed.
double s_offset = s_at_max_kappa - init_s[0];
double t = 2.0 * s_offset / (v_init + v_end);
if (t < FLAGS_double_precision) {
return {v_init, FLAGS_prediction_trajectory_time_length};
}
// If the deceleration is too much,
// then predict the obstacle follows a reasonable deceleration.
double acc = (v_end - v_init) / t;
if (acc < FLAGS_vehicle_min_linear_acc) {
t = v_init / (-FLAGS_vehicle_min_linear_acc);
return {FLAGS_still_obstacle_speed_threshold, t};
}
// Otherwise, predict that it takes t for the obstacle to arrive at the
// max. curvature point with v_end speed.
return {v_end, t};
}
double MoveSequencePredictor::ComputeTimeToLatEndConditionByVelocity(
const Obstacle& obstacle, const LaneSequence& lane_sequence) {
// Sanity check.
CHECK_GT(obstacle.history_size(), 0U);
CHECK_GT(lane_sequence.lane_segment_size(), 0);
CHECK_GT(lane_sequence.lane_segment(0).lane_point_size(), 0);
// Get the obstacle's Cartesian v_x, v_y.
// Get the lane point's Cartesian angle, relative distance.
// Then project the obstacle's velocity onto Frenet coordinate to get
// lateral velocity v_l.
const Feature& feature = obstacle.latest_feature();
const LanePoint& first_lane_point =
lane_sequence.lane_segment(0).lane_point(0);
double v_x = feature.velocity().x();
double v_y = feature.velocity().y();
double lane_heading = first_lane_point.heading();
double lane_l = first_lane_point.relative_l();
double v_l = v_y * std::cos(lane_heading) - v_x * std::sin(lane_heading);
// If laterally moving too slow or even away from lane center,
// then use the default speed
// Otherwise, directly calculate the time and return.
if (std::fabs(v_l) < FLAGS_default_lateral_approach_speed ||
lane_l * v_l < 0.0) {
return std::fabs(lane_l / FLAGS_default_lateral_approach_speed);
}
return std::fabs(lane_l / v_l);
}
std::vector<double> MoveSequencePredictor::GenerateCandidateTimes() {
std::vector<double> candidate_times;
double t = FLAGS_time_lower_bound_to_lane_center;
double time_gap = FLAGS_sample_time_gap;
while (t <= FLAGS_time_upper_bound_to_lane_center) {
candidate_times.push_back(t);
t += time_gap;
}
return candidate_times;
}
double MoveSequencePredictor::CostFunction(const double max_lat_acc,
const double time_to_end_state,
const double time_to_lane_edge,
const double bell_curve_mu) {
double cost_of_trajectory =
max_lat_acc + FLAGS_cost_function_alpha * time_to_end_state;
if (FLAGS_use_bell_curve_for_cost_function) {
double bell_curve_weight =
1.0 /
std::sqrt(2.0 * M_PI * FLAGS_cost_function_sigma *
FLAGS_cost_function_sigma) *
std::exp(-(time_to_lane_edge - bell_curve_mu) *
(time_to_lane_edge - bell_curve_mu) /
(2.0 * FLAGS_cost_function_sigma * FLAGS_cost_function_sigma));
cost_of_trajectory /= (bell_curve_weight + FLAGS_double_precision);
}
return cost_of_trajectory;
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/move_sequence/move_sequence_predictor.h
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define move sequence predictor
*/
#pragma once
#include <string>
#include <utility>
#include <vector>
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
namespace apollo {
namespace prediction {
class MoveSequencePredictor : public SequencePredictor {
public:
/**
* @brief Constructor
*/
MoveSequencePredictor();
/**
* @brief Destructor
*/
virtual ~MoveSequencePredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
FRIEND_TEST(MoveSequencePredictorTest, Polynomial);
FRIEND_TEST(MoveSequencePredictorTest, Utils);
private:
bool DrawMoveSequenceTrajectoryPoints(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period,
std::vector<apollo::common::TrajectoryPoint>* points);
std::pair<double, double> ComputeLonEndState(
const std::array<double, 3>& init_s, const LaneSequence& lane_sequence);
double ComputeTimeToLatEndConditionByVelocity(
const Obstacle& obstacle, const LaneSequence& lane_sequence);
std::vector<double> GenerateCandidateTimes();
double CostFunction(const double max_lat_acc, const double time_to_end_state,
const double time_to_lane_edge,
const double bell_curve_mu);
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/move_sequence/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "move_sequence_predictor",
srcs = ["move_sequence_predictor.cc"],
hdrs = ["move_sequence_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/common:prediction_util",
"//modules/prediction/predictor/sequence:sequence_predictor",
],
)
cc_test(
name = "move_sequence_predictor_test",
size = "small",
srcs = ["move_sequence_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/evaluator/vehicle:mlp_evaluator",
"//modules/prediction/predictor/move_sequence:move_sequence_predictor",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/move_sequence/move_sequence_predictor_test.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/move_sequence/move_sequence_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/mlp_evaluator.h"
namespace apollo {
namespace prediction {
class MoveSequencePredictorTest : public KMLMapBasedTest {
public:
virtual void SetUp() {
const std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
cyber::common::GetProtoFromFile(file, &perception_obstacles_);
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(MoveSequencePredictorTest, OnLaneCase) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator mlp_evaluator;
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
container.BuildLaneGraph();
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
mlp_evaluator.Evaluate(obstacle_ptr, &container);
MoveSequencePredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 1);
}
TEST_F(MoveSequencePredictorTest, Polynomial) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator mlp_evaluator;
ObstaclesContainer container;
container.Insert(perception_obstacles_);
container.BuildLaneGraph();
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
mlp_evaluator.Evaluate(obstacle_ptr, &container);
MoveSequencePredictor predictor;
const Feature& feature = obstacle_ptr->latest_feature();
const LaneGraph& lane_graph = feature.lane().lane_graph();
for (const auto& lane_sequence : lane_graph.lane_sequence()) {
std::pair<double, double> lon_end_state = {3.0, 3.0};
std::array<double, 5> lon_coefficients;
bool ret_lon = predictor.GetLongitudinalPolynomial(
*obstacle_ptr, lane_sequence, lon_end_state, &lon_coefficients);
EXPECT_TRUE(ret_lon);
std::array<double, 4> lat_coefficients;
bool ret_lat = predictor.GetLateralPolynomial(*obstacle_ptr, lane_sequence,
3.0, &lat_coefficients);
EXPECT_TRUE(ret_lat);
}
}
TEST_F(MoveSequencePredictorTest, Utils) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator mlp_evaluator;
ObstaclesContainer container;
container.Insert(perception_obstacles_);
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
mlp_evaluator.Evaluate(obstacle_ptr, &container);
MoveSequencePredictor predictor;
const Feature& feature = obstacle_ptr->latest_feature();
const LaneGraph& lane_graph = feature.lane().lane_graph();
for (const auto& lane_sequence : lane_graph.lane_sequence()) {
double speed = predictor.ComputeTimeToLatEndConditionByVelocity(
*obstacle_ptr, lane_sequence);
EXPECT_GT(speed, 0.0);
}
std::vector<double> candidate_times = predictor.GenerateCandidateTimes();
EXPECT_GT(candidate_times.size(), 0);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/junction/junction_predictor.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/junction/junction_predictor.h"
#include <algorithm>
#include <limits>
#include <memory>
#include <utility>
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/prediction_util.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::TrajectoryPoint;
using apollo::hdmap::LaneInfo;
using apollo::prediction::math_util::ComputePolynomial;
using apollo::prediction::math_util::EvaluateCubicPolynomial;
JunctionPredictor::JunctionPredictor() {
predictor_type_ = ObstacleConf::JUNCTION_PREDICTOR;
}
bool JunctionPredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
obstacle->SetPredictorType(predictor_type_);
const Feature& latest_feature = obstacle->latest_feature();
std::vector<JunctionExit> junction_exits =
MostLikelyJunctions(latest_feature);
for (const auto& junction_exit : junction_exits) {
std::vector<TrajectoryPoint> trajectory_points;
DrawJunctionTrajectoryPoints(
latest_feature, junction_exit, FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, &trajectory_points);
Trajectory trajectory = GenerateTrajectory(trajectory_points);
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
}
return true;
}
void JunctionPredictor::DrawJunctionTrajectoryPoints(
const Feature& feature, const JunctionExit& junction_exit,
const double total_time, const double period,
std::vector<TrajectoryPoint>* trajectory_points) {
double speed = feature.speed();
const std::array<double, 2> start_x = {feature.position().x(),
feature.raw_velocity().x()};
const std::array<double, 2> end_x = {
junction_exit.exit_position().x(),
std::cos(junction_exit.exit_heading()) * speed};
const std::array<double, 2> start_y = {feature.position().y(),
feature.raw_velocity().y()};
const std::array<double, 2> end_y = {
junction_exit.exit_position().y(),
std::sin(junction_exit.exit_heading()) * speed};
double exit_time = GetBestTime(start_x, end_x, start_y, end_y);
std::array<double, 4> x_coeffs =
ComputePolynomial<3>(start_x, end_x, exit_time);
std::array<double, 4> y_coeffs =
ComputePolynomial<3>(start_y, end_y, exit_time);
double t = 0.0;
// Trajectory in junction
while (t <= exit_time) {
PathPoint path_point;
path_point.set_x(EvaluateCubicPolynomial(x_coeffs, t, 0));
path_point.set_y(EvaluateCubicPolynomial(y_coeffs, t, 0));
path_point.set_z(0.0);
path_point.set_theta(std::atan2(EvaluateCubicPolynomial(y_coeffs, t, 1),
EvaluateCubicPolynomial(x_coeffs, t, 1)));
TrajectoryPoint trajectory_point;
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(std::hypot(EvaluateCubicPolynomial(x_coeffs, t, 1),
EvaluateCubicPolynomial(y_coeffs, t, 1)));
trajectory_point.set_relative_time(t);
trajectory_points->emplace_back(std::move(trajectory_point));
t += period;
}
std::string lane_id = junction_exit.exit_lane_id();
std::shared_ptr<const LaneInfo> lane_info = PredictionMap::LaneById(lane_id);
Eigen::Vector2d pos(junction_exit.exit_position().x(),
junction_exit.exit_position().y());
double lane_s = 0.0;
double lane_l = 0.0;
double theta = M_PI;
PredictionMap::GetProjection(pos, lane_info, &lane_s, &lane_l);
// Trajectory after junction
while (t <= total_time) {
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, 0.0, &pos,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << 0.0 << "]";
return;
}
TrajectoryPoint trajectory_point;
PathPoint path_point;
path_point.set_x(pos.x());
path_point.set_y(pos.y());
path_point.set_z(0.0);
path_point.set_theta(theta);
path_point.set_lane_id(lane_id);
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(speed);
trajectory_point.set_a(0.0);
trajectory_point.set_relative_time(t);
trajectory_points->emplace_back(std::move(trajectory_point));
lane_s += speed * period;
while (lane_s > PredictionMap::LaneById(lane_id)->total_length()) {
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
if (PredictionMap::LaneById(lane_id)->lane().successor_id_size() < 1) {
return;
}
// TODO(all) consider the logic to choose successor_id
lane_id = PredictionMap::LaneById(lane_id)->lane().successor_id(0).id();
}
t += period;
}
}
std::vector<JunctionExit> JunctionPredictor::MostLikelyJunctions(
const Feature& feature) {
if (!feature.has_junction_feature()) {
AERROR << "No junction_feature exist!";
return {};
}
if (feature.junction_feature().junction_exit_size() < 1 ||
feature.junction_feature().junction_mlp_probability_size() != 12) {
AERROR << "No junction_exit"
<< "or no enough junction_mlp_probability to process!";
return {};
}
int max_idx = 0;
double max_prob = 0.0;
for (int i = 0; i < 12; ++i) {
if (feature.junction_feature().junction_mlp_probability(i) > max_prob) {
max_prob = feature.junction_feature().junction_mlp_probability(i);
max_idx = i;
}
}
std::vector<JunctionExit> junction_exits;
for (const JunctionExit& junction_exit :
feature.junction_feature().junction_exit()) {
double x = junction_exit.exit_position().x() - feature.position().x();
double y = junction_exit.exit_position().y() - feature.position().y();
double angle = std::atan2(y, x) - std::atan2(feature.raw_velocity().y(),
feature.raw_velocity().x());
double d_idx = (angle / (2.0 * M_PI)) * 12.0;
int idx = static_cast<int>(floor(d_idx >= 0 ? d_idx : d_idx + 12));
if (idx == max_idx) {
junction_exits.push_back(junction_exit);
}
}
return junction_exits;
}
double JunctionPredictor::GetBestTime(const std::array<double, 2>& start_x,
const std::array<double, 2>& end_x,
const std::array<double, 2>& start_y,
const std::array<double, 2>& end_y) {
// Generate candidate finish times.
std::vector<double> candidate_times = GenerateCandidateTimes();
double best_time = 0.0;
double best_cost = std::numeric_limits<double>::infinity();
for (size_t i = 0; i < candidate_times.size(); ++i) {
double time_to_exit = candidate_times[i];
std::array<double, 4> x_coeffs =
ComputePolynomial<3>(start_x, end_x, time_to_exit);
std::array<double, 4> y_coeffs =
ComputePolynomial<3>(start_y, end_y, time_to_exit);
double cost_of_trajectory = CostFunction(x_coeffs, y_coeffs, time_to_exit);
if (cost_of_trajectory <= best_cost) {
best_cost = cost_of_trajectory;
best_time = time_to_exit;
}
}
return best_time;
}
double JunctionPredictor::CostFunction(const std::array<double, 4>& x_coeffs,
const std::array<double, 4>& y_coeffs,
const double time_to_exit) {
double t = 0.0;
double cost = 0.0;
while (t <= time_to_exit) {
double x_1 = EvaluateCubicPolynomial(x_coeffs, t, 1);
double x_2 = EvaluateCubicPolynomial(x_coeffs, t, 2);
double y_1 = EvaluateCubicPolynomial(y_coeffs, t, 1);
double y_2 = EvaluateCubicPolynomial(y_coeffs, t, 2);
// cost = curvature * v^2 + time_to_exit
cost =
std::max(cost, std::abs(x_1 * y_2 - y_1 * x_2) / std::hypot(x_1, y_1) +
time_to_exit);
t += FLAGS_prediction_trajectory_time_resolution;
}
return cost;
}
std::vector<double> JunctionPredictor::GenerateCandidateTimes() {
std::vector<double> candidate_times;
double t = 1.0;
double time_gap = 0.5;
while (t <= FLAGS_prediction_trajectory_time_length) {
candidate_times.push_back(t);
t += time_gap;
}
return candidate_times;
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/junction/junction_predictor_test.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/junction/junction_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/junction_analyzer.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/junction_mlp_evaluator.h"
namespace apollo {
namespace prediction {
class JunctionPredictorTest : public KMLMapBasedTest {
public:
void SetUp() override {
const std::string file =
"modules/prediction/testdata/"
"single_perception_vehicle_injunction.pb.txt";
ACHECK(cyber::common::GetProtoFromFile(file, &perception_obstacles_));
FLAGS_enable_all_junction = true;
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(JunctionPredictorTest, InJunctionCase) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
JunctionMLPEvaluator junction_mlp_evaluator;
ObstaclesContainer container;
container.GetJunctionAnalyzer()->Init("j2");
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
container.BuildJunctionFeature();
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
junction_mlp_evaluator.Evaluate(obstacle_ptr, &container);
JunctionPredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
// EXPECT_EQ(predictor.NumOfTrajectories(), 2);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/junction/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "junction_predictor",
srcs = ["junction_predictor.cc"],
hdrs = ["junction_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/common:prediction_util",
"//modules/prediction/predictor",
],
)
cc_test(
name = "junction_predictor_test",
size = "small",
srcs = ["junction_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
linkopts = [
"-lgomp",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/container/obstacles:obstacles_container",
"//modules/prediction/evaluator/vehicle:junction_mlp_evaluator",
"//modules/prediction/predictor/junction:junction_predictor",
"@com_google_googletest//:gtest_main",
],
linkstatic = True,
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/junction/junction_predictor.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define junction predictor
*/
#pragma once
#include <string>
#include <vector>
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/predictor/predictor.h"
namespace apollo {
namespace prediction {
class JunctionPredictor : public Predictor {
public:
/**
* @brief Constructor
*/
JunctionPredictor();
/**
* @brief Destructor
*/
virtual ~JunctionPredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
private:
void DrawJunctionTrajectoryPoints(
const Feature& feature, const JunctionExit& junction_exit,
const double total_time, const double period,
std::vector<apollo::common::TrajectoryPoint>* trajectory_points);
std::vector<JunctionExit> MostLikelyJunctions(const Feature& feature);
/**
* @brief Get best pass time
* @param start_x, end_x, start_y, end_y
*/
double GetBestTime(const std::array<double, 2>& start_x,
const std::array<double, 2>& end_x,
const std::array<double, 2>& start_y,
const std::array<double, 2>& end_y);
double CostFunction(const std::array<double, 4>& x_coeffs,
const std::array<double, 4>& y_coeffs,
const double time_to_exit);
std::vector<double> GenerateCandidateTimes();
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/free_move/free_move_predictor_test.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/free_move/free_move_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
namespace apollo {
namespace prediction {
class FreeMovePredictorTest : public KMLMapBasedTest {
public:
FreeMovePredictorTest() {
ACHECK(cyber::common::GetProtoFromFile(
"modules/prediction/testdata/single_perception_vehicle_offlane.pb.txt",
&perception_obstacles_));
FLAGS_p_var = 0.1;
FLAGS_q_var = 0.01;
FLAGS_r_var = 0.25;
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(FreeMovePredictorTest, General) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 15);
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
Obstacle* obstacle_ptr = container.GetObstacle(15);
EXPECT_NE(obstacle_ptr, nullptr);
FreeMovePredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 1);
}
TEST_F(FreeMovePredictorTest, Pedestrian) {
perception_obstacles_.mutable_perception_obstacle(0)->set_type(
::apollo::perception::PerceptionObstacle::PEDESTRIAN);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
Obstacle* obstacle_ptr = container.GetObstacle(15);
FreeMovePredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 1);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/free_move/free_move_predictor.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/free_move/free_move_predictor.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/prediction_util.h"
#include "modules/prediction/proto/prediction_conf.pb.h"
namespace apollo {
namespace prediction {
using apollo::common::TrajectoryPoint;
using apollo::perception::PerceptionObstacle;
FreeMovePredictor::FreeMovePredictor() {
predictor_type_ = ObstacleConf::FREE_MOVE_PREDICTOR;
}
bool FreeMovePredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
obstacle->SetPredictorType(predictor_type_);
const Feature& feature = obstacle->latest_feature();
if (!feature.has_position() || !feature.has_velocity() ||
!feature.position().has_x() || !feature.position().has_y()) {
AERROR << "Obstacle [" << obstacle->id()
<< " is missing position or velocity";
return false;
}
double prediction_total_time = FLAGS_prediction_trajectory_time_length;
if (obstacle->type() == PerceptionObstacle::PEDESTRIAN) {
prediction_total_time = FLAGS_prediction_trajectory_time_length;
}
if (feature.predicted_trajectory().empty()) {
std::vector<TrajectoryPoint> points;
Eigen::Vector2d position(feature.position().x(), feature.position().y());
Eigen::Vector2d velocity(feature.velocity().x(), feature.velocity().y());
Eigen::Vector2d acc(feature.acceleration().x(), feature.acceleration().y());
double theta = feature.velocity_heading();
DrawFreeMoveTrajectoryPoints(
position, velocity, acc, theta, 0.0, prediction_total_time,
FLAGS_prediction_trajectory_time_resolution, &points);
Trajectory trajectory = GenerateTrajectory(points);
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
SetEqualProbability(1.0, 0, obstacle);
} else {
for (int i = 0; i < feature.predicted_trajectory_size(); ++i) {
Trajectory* trajectory =
obstacle->mutable_latest_feature()->mutable_predicted_trajectory(i);
int traj_size = trajectory->trajectory_point_size();
if (traj_size == 0) {
AERROR << "Empty predicted trajectory found";
continue;
}
std::vector<TrajectoryPoint> points;
const TrajectoryPoint& last_point =
trajectory->trajectory_point(traj_size - 1);
double theta = last_point.path_point().theta();
Eigen::Vector2d position(last_point.path_point().x(),
last_point.path_point().y());
Eigen::Vector2d velocity(last_point.v() * std::cos(theta),
last_point.v() * std::sin(theta));
Eigen::Vector2d acc(last_point.a() * std::cos(theta),
last_point.a() * std::sin(theta));
double last_relative_time = last_point.relative_time();
DrawFreeMoveTrajectoryPoints(
position, velocity, acc, theta, last_relative_time,
prediction_total_time - last_relative_time,
FLAGS_prediction_trajectory_time_resolution, &points);
// The following for-loop starts from index 1 because the vector points
// includes the last point in the existing predicted trajectory
for (size_t i = 1; i < points.size(); ++i) {
trajectory->add_trajectory_point()->CopyFrom(points[i]);
}
}
}
return true;
}
void FreeMovePredictor::DrawFreeMoveTrajectoryPoints(
const Eigen::Vector2d& position, const Eigen::Vector2d& velocity,
const Eigen::Vector2d& acc, const double theta, const double start_time,
const double total_time, const double period,
std::vector<TrajectoryPoint>* points) {
Eigen::Matrix<double, 6, 1> state;
state.setZero();
state(0, 0) = 0.0;
state(1, 0) = 0.0;
state(2, 0) = velocity(0);
state(3, 0) = velocity(1);
state(4, 0) = common::math::Clamp(acc(0), FLAGS_vehicle_min_linear_acc,
FLAGS_vehicle_max_linear_acc);
state(5, 0) = common::math::Clamp(acc(1), FLAGS_vehicle_min_linear_acc,
FLAGS_vehicle_max_linear_acc);
Eigen::Matrix<double, 6, 6> transition;
transition.setIdentity();
transition(0, 2) = period;
transition(0, 4) = 0.5 * period * period;
transition(1, 3) = period;
transition(1, 5) = 0.5 * period * period;
transition(2, 4) = period;
transition(3, 5) = period;
size_t num = static_cast<size_t>(total_time / period);
::apollo::prediction::predictor_util::GenerateFreeMoveTrajectoryPoints(
&state, transition, theta, start_time, num, period, points);
for (size_t i = 0; i < points->size(); ++i) {
::apollo::prediction::predictor_util::TranslatePoint(
position[0], position[1], &(points->operator[](i)));
}
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/free_move/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "free_move_predictor",
srcs = ["free_move_predictor.cc"],
hdrs = ["free_move_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/common:prediction_util",
"//modules/prediction/container/obstacles:obstacles_container",
"//modules/prediction/predictor",
],
)
cc_test(
name = "free_move_predictor_test",
size = "small",
srcs = ["free_move_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/predictor/free_move:free_move_predictor",
"@com_google_googletest//:gtest_main",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/free_move/free_move_predictor.h
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define lane sequence predictor
*/
#pragma once
#include <vector>
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/predictor/predictor.h"
namespace apollo {
namespace prediction {
class FreeMovePredictor : public Predictor {
public:
/**
* @brief Constructor
*/
FreeMovePredictor();
/**
* @brief Destructor
*/
virtual ~FreeMovePredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
private:
/**
* @brief Generate free move trajectory
* @param Position
* @param Velocity
* @param Acceleration
* @param Kalman Filter
* @param start time
* @param Total time
* @param Generated trajectory points
*/
void DrawFreeMoveTrajectoryPoints(
const Eigen::Vector2d& position, const Eigen::Vector2d& velocity,
const Eigen::Vector2d& acc, const double theta, const double start_time,
const double total_time, const double period,
std::vector<apollo::common::TrajectoryPoint>* points);
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/extrapolation/extrapolation_predictor.h
|
/******************************************************************************
* Copyright 2019 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define extrapolation predictor
*/
#pragma once
#include <string>
#include "modules/prediction/container/obstacles/obstacle_clusters.h"
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
namespace apollo {
namespace prediction {
class ExtrapolationPredictor : public SequencePredictor {
public:
/**
* @brief Constructor
*/
ExtrapolationPredictor();
/**
* @brief Destructor
*/
virtual ~ExtrapolationPredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
private:
struct LaneSearchResult {
bool found = false;
std::string lane_id = "";
int point_index = -1;
};
void PostProcess(Trajectory* trajectory_ptr, ObstacleClusters* clusters_ptr);
LaneSearchResult SearchExtrapolationLane(const Trajectory& trajectory,
const int num_tail_point);
void ExtrapolateByLane(const LaneSearchResult& lane_search_result,
const double extrapolation_speed,
Trajectory* trajectory_ptr,
ObstacleClusters* clusters_ptr);
void ExtrapolateByFreeMove(const int num_tail_point,
const double extrapolation_speed,
Trajectory* trajectory_ptr);
double ComputeExtraplationSpeed(const int num_tail_point,
const Trajectory& trajectory);
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/extrapolation/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "extrapolation_predictor",
srcs = ["extrapolation_predictor.cc"],
hdrs = ["extrapolation_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/common/math",
"//modules/prediction/common:prediction_gflags",
"//modules/prediction/common:prediction_map",
"//modules/prediction/common:prediction_util",
"//modules/prediction/container/obstacles:obstacle_clusters",
"//modules/prediction/container/obstacles:obstacles_container",
"//modules/prediction/predictor/sequence:sequence_predictor",
"//modules/common_msgs/prediction_msgs:lane_graph_cc_proto",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/extrapolation/extrapolation_predictor.cc
|
/******************************************************************************
* Copyright 2019 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/extrapolation/extrapolation_predictor.h"
#include "modules/common/math/vec2d.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/prediction_map.h"
#include "modules/common_msgs/prediction_msgs/lane_graph.pb.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::TrajectoryPoint;
ExtrapolationPredictor::ExtrapolationPredictor() {
predictor_type_ = ObstacleConf::EXTRAPOLATION_PREDICTOR;
}
bool ExtrapolationPredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
obstacle->SetPredictorType(predictor_type_);
Feature* feature_ptr = obstacle->mutable_latest_feature();
if (!feature_ptr->lane().has_lane_graph()) {
AERROR << "Obstacle [" << obstacle->id() << "] has no lane graph.";
return false;
}
if (feature_ptr->predicted_trajectory().empty()) {
AERROR << "Obstacle [" << obstacle->id()
<< "] has no short-term trajectories.";
return false;
}
auto* cluster_ptr = obstacles_container->GetClustersPtr();
for (int i = 0; i < feature_ptr->predicted_trajectory_size(); ++i) {
Trajectory* trajectory_ptr = feature_ptr->mutable_predicted_trajectory(i);
PostProcess(trajectory_ptr, cluster_ptr);
}
return true;
}
void ExtrapolationPredictor::PostProcess(Trajectory* trajectory_ptr,
ObstacleClusters* clusters_ptr) {
// TODO(kechxu) handle corner cases
static constexpr int kNumTailPoint = 5;
ExtrapolationPredictor::LaneSearchResult lane_search_result =
SearchExtrapolationLane(*trajectory_ptr, kNumTailPoint);
double extraplation_speed =
ComputeExtraplationSpeed(kNumTailPoint, *trajectory_ptr);
if (lane_search_result.found) {
ExtrapolateByLane(lane_search_result, extraplation_speed, trajectory_ptr,
clusters_ptr);
} else {
ExtrapolateByFreeMove(kNumTailPoint, extraplation_speed, trajectory_ptr);
}
}
ExtrapolationPredictor::LaneSearchResult
ExtrapolationPredictor::SearchExtrapolationLane(const Trajectory& trajectory,
const int num_tail_point) {
static constexpr double radius = 1.0;
static constexpr double angle_diff_threshold = M_PI / 3.0;
int num_trajectory_point = trajectory.trajectory_point_size();
LaneSearchResult lane_search_result;
for (int i = num_trajectory_point - 1;
i >= num_trajectory_point - num_tail_point; --i) {
const TrajectoryPoint& trajectory_point = trajectory.trajectory_point(i);
const PathPoint& path_point = trajectory_point.path_point();
apollo::common::PointENU point_enu;
point_enu.set_x(path_point.x());
point_enu.set_y(path_point.y());
double heading = path_point.theta();
auto lane_info_ptr = PredictionMap::GetMostLikelyCurrentLane(
point_enu, radius, heading, angle_diff_threshold);
if (lane_info_ptr != nullptr) {
lane_search_result.found = true;
lane_search_result.lane_id = lane_info_ptr->lane().id().id();
lane_search_result.point_index = i;
break;
}
}
return lane_search_result;
}
void ExtrapolationPredictor::ExtrapolateByLane(
const LaneSearchResult& lane_search_result, const double extraplation_speed,
Trajectory* trajectory_ptr, ObstacleClusters* clusters_ptr) {
std::string start_lane_id = lane_search_result.lane_id;
int point_index = lane_search_result.point_index;
while (trajectory_ptr->trajectory_point_size() > point_index + 1) {
trajectory_ptr->mutable_trajectory_point()->RemoveLast();
}
auto lane_info_ptr = PredictionMap::LaneById(start_lane_id);
int num_trajectory_point = trajectory_ptr->trajectory_point_size();
const TrajectoryPoint& last_point =
trajectory_ptr->trajectory_point(num_trajectory_point - 1);
Eigen::Vector2d position(last_point.path_point().x(),
last_point.path_point().y());
double lane_s = 0.0;
double lane_l = 0.0;
bool projected =
PredictionMap::GetProjection(position, lane_info_ptr, &lane_s, &lane_l);
if (!projected) {
AERROR << "Position (" << position.x() << ", " << position.y() << ") "
<< "cannot be projected onto lane [" << start_lane_id << "]";
return;
}
double last_relative_time = last_point.relative_time();
double time_range =
FLAGS_prediction_trajectory_time_length - last_relative_time;
double time_resolution = FLAGS_prediction_trajectory_time_resolution;
double length = extraplation_speed * time_range;
LaneGraph lane_graph =
clusters_ptr->GetLaneGraph(lane_s, length, false, lane_info_ptr);
CHECK_EQ(lane_graph.lane_sequence_size(), 1);
const LaneSequence& lane_sequence = lane_graph.lane_sequence(0);
int lane_segment_index = 0;
std::string lane_id =
lane_sequence.lane_segment(lane_segment_index).lane_id();
int num_point_remained = static_cast<int>(time_range / time_resolution);
for (int i = 1; i <= num_point_remained; ++i) {
double relative_time =
last_relative_time + static_cast<double>(i) * time_resolution;
Eigen::Vector2d point;
double theta = M_PI;
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, lane_l, &point,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << lane_l << "]";
break;
}
TrajectoryPoint* trajectory_point = trajectory_ptr->add_trajectory_point();
PathPoint* path_point = trajectory_point->mutable_path_point();
path_point->set_x(point.x());
path_point->set_y(point.y());
path_point->set_z(0.0);
path_point->set_theta(theta);
path_point->set_lane_id(lane_id);
trajectory_point->set_v(extraplation_speed);
trajectory_point->set_a(0.0);
trajectory_point->set_relative_time(relative_time);
lane_s += extraplation_speed * time_resolution;
while (lane_s > PredictionMap::LaneById(lane_id)->total_length() &&
lane_segment_index + 1 < lane_sequence.lane_segment_size()) {
lane_segment_index += 1;
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
lane_id = lane_sequence.lane_segment(lane_segment_index).lane_id();
}
lane_l *= FLAGS_go_approach_rate;
}
}
void ExtrapolationPredictor::ExtrapolateByFreeMove(
const int num_tail_point, const double extraplation_speed,
Trajectory* trajectory_ptr) {
int num_trajectory_point = trajectory_ptr->trajectory_point_size();
const TrajectoryPoint& last_point =
trajectory_ptr->trajectory_point(num_trajectory_point - 1);
double theta = last_point.path_point().theta();
double time_resolution = FLAGS_prediction_trajectory_time_resolution;
double time_length = FLAGS_prediction_trajectory_time_length;
double relative_time = last_point.relative_time() + time_resolution;
while (relative_time < time_length) {
int prev_size = trajectory_ptr->trajectory_point_size();
const TrajectoryPoint& prev_point =
trajectory_ptr->trajectory_point(prev_size - 1);
TrajectoryPoint* curr_point = trajectory_ptr->add_trajectory_point();
double dx = time_resolution * extraplation_speed * std::cos(theta);
double dy = time_resolution * extraplation_speed * std::sin(theta);
double curr_x = prev_point.path_point().x() + dx;
double curr_y = prev_point.path_point().y() + dy;
PathPoint* curr_path_point_ptr = curr_point->mutable_path_point();
curr_path_point_ptr->set_x(curr_x);
curr_path_point_ptr->set_y(curr_y);
curr_path_point_ptr->set_theta(theta);
curr_point->set_v(extraplation_speed);
curr_point->set_relative_time(relative_time);
relative_time += time_resolution;
}
}
double ExtrapolationPredictor::ComputeExtraplationSpeed(
const int num_tail_point, const Trajectory& trajectory) {
int num_trajectory_point = trajectory.trajectory_point_size();
CHECK_GT(num_trajectory_point, num_tail_point);
CHECK_GT(num_tail_point, 0);
double v_sum = 0.0;
int mid_index = num_trajectory_point - num_tail_point;
for (int i = mid_index; i < num_trajectory_point; ++i) {
v_sum += trajectory.trajectory_point(i).v();
}
return v_sum / static_cast<double>(num_tail_point);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/sequence/sequence_predictor.cc
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
#include <limits>
#include <memory>
#include "modules/common_msgs/basic_msgs/geometry.pb.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/container/container_manager.h"
#include "modules/prediction/container/pose/pose_container.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::Point3D;
using apollo::common::TrajectoryPoint;
using apollo::hdmap::LaneInfo;
bool SequencePredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
return true;
}
void SequencePredictor::Clear() { Predictor::Clear(); }
std::string SequencePredictor::ToString(const LaneSequence& sequence) {
std::string str_lane_sequence = "";
if (sequence.lane_segment_size() > 0) {
str_lane_sequence += sequence.lane_segment(0).lane_id();
}
for (int i = 1; i < sequence.lane_segment_size(); ++i) {
str_lane_sequence += ("->" + sequence.lane_segment(i).lane_id());
}
return str_lane_sequence;
}
void SequencePredictor::FilterLaneSequences(
const Feature& feature, const std::string& lane_id,
const Obstacle* ego_vehicle_ptr,
const ADCTrajectoryContainer* adc_trajectory_container,
std::vector<bool>* enable_lane_sequence) {
if (!feature.has_lane() || !feature.lane().has_lane_graph()) {
return;
}
const LaneGraph& lane_graph = feature.lane().lane_graph();
int num_lane_sequence = lane_graph.lane_sequence_size();
std::vector<LaneChangeType> lane_change_type(num_lane_sequence,
LaneChangeType::INVALID);
std::pair<int, double> change(-1, -1.0);
std::pair<int, double> all(-1, -1.0);
/**
* Filter out those obstacles that are close to the ADC
* so that we will ignore them and drive normally unless
* they really kick into our lane.
*/
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& sequence = lane_graph.lane_sequence(i);
if (sequence.lane_type() == apollo::hdmap::Lane::PARKING) {
(*enable_lane_sequence)[i] = false;
ADEBUG << "Ignore lane sequence [" << ToString(sequence) << "].";
continue;
}
lane_change_type[i] = GetLaneChangeType(lane_id, sequence);
if (lane_change_type[i] != LaneChangeType::LEFT &&
lane_change_type[i] != LaneChangeType::RIGHT &&
lane_change_type[i] != LaneChangeType::ONTO_LANE) {
ADEBUG << "Ignore lane sequence [" << ToString(sequence) << "].";
continue;
}
// The obstacle has interference with ADC within a small distance
double distance = GetLaneChangeDistanceWithADC(sequence, ego_vehicle_ptr,
adc_trajectory_container);
ADEBUG << "Distance to ADC " << std::fixed << std::setprecision(6)
<< distance;
if (distance > 0.0 && distance < FLAGS_lane_change_dist) {
bool obs_within_its_own_lane = true;
for (int j = 0; j < feature.polygon_point_size(); j++) {
Eigen::Vector2d position(feature.polygon_point(j).x(),
feature.polygon_point(j).y());
std::shared_ptr<const LaneInfo> lane_info =
PredictionMap::LaneById(lane_id);
if (lane_info == nullptr) {
obs_within_its_own_lane = false;
break;
}
double lane_s = 0.0;
double lane_l = 0.0;
PredictionMap::GetProjection(position, lane_info, &lane_s, &lane_l);
double left = 0.0;
double right = 0.0;
lane_info->GetWidth(lane_s, &left, &right);
if (lane_l > left || lane_l < -right) {
obs_within_its_own_lane = false;
break;
}
}
if (obs_within_its_own_lane) {
(*enable_lane_sequence)[i] = false;
ADEBUG << "Filter trajectory [" << ToString(sequence)
<< "] due to small distance " << distance << ".";
}
}
}
/**
* Pick the most probable lane-sequence and lane-change
*/
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& sequence = lane_graph.lane_sequence(i);
if (!(*enable_lane_sequence)[i]) {
ADEBUG << "Disabled lane sequence [" << ToString(sequence) << "].";
continue;
}
double probability = sequence.probability();
if (LaneSequenceWithMaxProb(lane_change_type[i], probability, all.second)) {
all.first = i;
all.second = probability;
}
if (LaneChangeWithMaxProb(lane_change_type[i], probability,
change.second)) {
change.first = i;
change.second = probability;
}
}
double lane_sequence_threshold = FLAGS_lane_sequence_threshold_cruise;
if (feature.has_junction_feature()) {
lane_sequence_threshold = FLAGS_lane_sequence_threshold_junction;
}
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& sequence = lane_graph.lane_sequence(i);
if (!(*enable_lane_sequence)[i]) {
ADEBUG << "Disabled lane sequence [" << ToString(sequence) << "].";
continue;
}
double probability = sequence.probability();
if (probability < lane_sequence_threshold && i != all.first) {
(*enable_lane_sequence)[i] = false;
} else if (change.first >= 0 && change.first < num_lane_sequence &&
(lane_change_type[i] == LaneChangeType::LEFT ||
lane_change_type[i] == LaneChangeType::RIGHT) &&
lane_change_type[i] != lane_change_type[change.first]) {
(*enable_lane_sequence)[i] = false;
}
}
}
SequencePredictor::LaneChangeType SequencePredictor::GetLaneChangeType(
const std::string& lane_id, const LaneSequence& lane_sequence) {
if (lane_id.empty()) {
return LaneChangeType::ONTO_LANE;
}
std::string lane_change_id = lane_sequence.lane_segment(0).lane_id();
if (lane_id == lane_change_id) {
return LaneChangeType::STRAIGHT;
} else {
auto ptr_change_lane = PredictionMap::LaneById(lane_change_id);
auto ptr_current_lane = PredictionMap::LaneById(lane_id);
if (PredictionMap::IsLeftNeighborLane(ptr_change_lane, ptr_current_lane)) {
return LaneChangeType::LEFT;
} else if (PredictionMap::IsRightNeighborLane(ptr_change_lane,
ptr_current_lane)) {
return LaneChangeType::RIGHT;
}
}
return LaneChangeType::INVALID;
}
double SequencePredictor::GetLaneChangeDistanceWithADC(
const LaneSequence& lane_sequence, const Obstacle* ego_vehicle_ptr,
const ADCTrajectoryContainer* adc_trajectory_container) {
if (!adc_trajectory_container->HasOverlap(lane_sequence)) {
ADEBUG << "The sequence [" << ToString(lane_sequence)
<< "] has no overlap with ADC.";
return std::numeric_limits<double>::max();
}
Eigen::Vector2d adc_position;
if (ego_vehicle_ptr != nullptr && ego_vehicle_ptr->history_size() > 0) {
const auto& position = ego_vehicle_ptr->latest_feature().position();
adc_position[0] = position.x();
adc_position[1] = position.y();
std::string obstacle_lane_id = lane_sequence.lane_segment(0).lane_id();
double obstacle_lane_s = lane_sequence.lane_segment(0).start_s();
double lane_s = 0.0;
double lane_l = 0.0;
if (PredictionMap::GetProjection(adc_position,
PredictionMap::LaneById(obstacle_lane_id),
&lane_s, &lane_l)) {
ADEBUG << "Distance with ADC is " << std::fabs(lane_s - obstacle_lane_s);
return obstacle_lane_s - lane_s;
}
}
ADEBUG << "Invalid ADC pose.";
return std::numeric_limits<double>::max();
}
bool SequencePredictor::LaneSequenceWithMaxProb(const LaneChangeType& type,
const double probability,
const double max_prob) {
if (probability > max_prob) {
return true;
} else {
double prob_diff = std::fabs(probability - max_prob);
if (prob_diff <= std::numeric_limits<double>::epsilon() &&
type == LaneChangeType::STRAIGHT) {
return true;
}
}
return false;
}
bool SequencePredictor::LaneChangeWithMaxProb(const LaneChangeType& type,
const double probability,
const double max_prob) {
if (type == LaneChangeType::LEFT || type == LaneChangeType::RIGHT) {
if (probability > max_prob) {
return true;
}
}
return false;
}
void SequencePredictor::DrawConstantAccelerationTrajectory(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period, const double acceleration,
std::vector<TrajectoryPoint>* points) {
const Feature& feature = obstacle.latest_feature();
if (!feature.has_position() || !feature.has_velocity() ||
!feature.position().has_x() || !feature.position().has_y()) {
AERROR << "Obstacle [" << obstacle.id()
<< " is missing position or velocity";
return;
}
Eigen::Vector2d position(feature.position().x(), feature.position().y());
double speed = feature.speed();
int lane_segment_index = 0;
std::string lane_id =
lane_sequence.lane_segment(lane_segment_index).lane_id();
std::shared_ptr<const LaneInfo> lane_info = PredictionMap::LaneById(lane_id);
double lane_s = 0.0;
double lane_l = 0.0;
if (!PredictionMap::GetProjection(position, lane_info, &lane_s, &lane_l)) {
AERROR << "Failed in getting lane s and lane l";
return;
}
size_t total_num = static_cast<size_t>(total_time / period);
for (size_t i = 0; i < total_num; ++i) {
double relative_time = static_cast<double>(i) * period;
Eigen::Vector2d point;
double theta = M_PI;
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, lane_l, &point,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << lane_l << "]";
break;
}
TrajectoryPoint trajectory_point;
PathPoint path_point;
path_point.set_x(point.x());
path_point.set_y(point.y());
path_point.set_z(0.0);
path_point.set_theta(theta);
path_point.set_lane_id(lane_id);
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(speed);
trajectory_point.set_a(0.0);
trajectory_point.set_relative_time(relative_time);
points->emplace_back(std::move(trajectory_point));
if (speed < FLAGS_double_precision) {
continue;
}
lane_s += speed * period + 0.5 * acceleration * period * period;
speed += acceleration * period;
while (lane_s > PredictionMap::LaneById(lane_id)->total_length() &&
lane_segment_index + 1 < lane_sequence.lane_segment_size()) {
lane_segment_index += 1;
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
lane_id = lane_sequence.lane_segment(lane_segment_index).lane_id();
}
lane_l *= FLAGS_go_approach_rate;
}
}
double SequencePredictor::GetLaneSequenceCurvatureByS(
const LaneSequence& lane_sequence, const double s) {
CHECK_GT(lane_sequence.lane_segment_size(), 0);
double lane_s = s + lane_sequence.lane_segment(0).start_s();
for (const LaneSegment& lane_segment : lane_sequence.lane_segment()) {
std::string lane_id = lane_segment.lane_id();
std::shared_ptr<const LaneInfo> lane_info_ptr =
PredictionMap::LaneById(lane_id);
double lane_length = lane_info_ptr->total_length();
if (lane_s > lane_length + FLAGS_double_precision) {
lane_s -= lane_length;
} else {
return lane_info_ptr->Curvature(lane_s);
}
}
ADEBUG << "Outside lane sequence range, use 0.0 to approximate.";
return 0.0;
}
bool SequencePredictor::GetLongitudinalPolynomial(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const std::pair<double, double>& lon_end_vt,
std::array<double, 5>* coefficients) {
// Sanity check.
CHECK_NOTNULL(coefficients);
CHECK_GT(obstacle.history_size(), 0U);
CHECK_GT(lane_sequence.lane_segment_size(), 0);
CHECK_GT(lane_sequence.lane_segment(0).lane_point_size(), 0);
// Get obstacle info.
const Feature& feature = obstacle.latest_feature();
double theta = feature.velocity_heading();
double v = feature.speed();
double a = 0.0;
// Get lane info.
if (FLAGS_enable_lane_sequence_acc && lane_sequence.has_acceleration()) {
a = lane_sequence.acceleration();
}
int lane_seg_start_idx = lane_sequence.adc_lane_segment_idx();
int lane_point_start_idx =
lane_sequence.lane_segment(lane_seg_start_idx).adc_lane_point_idx();
if (lane_point_start_idx >=
lane_sequence.lane_segment(lane_seg_start_idx).lane_point_size()) {
lane_point_start_idx =
lane_sequence.lane_segment(lane_seg_start_idx).lane_point_size() - 1;
}
double lane_heading = lane_sequence.lane_segment(lane_seg_start_idx)
.lane_point(lane_point_start_idx)
.heading();
// Set the initial conditions for the diff. eqn.
double s0 = 0.0;
double ds0 = v * std::cos(theta - lane_heading);
double dds0 = a * std::cos(theta - lane_heading);
// double min_end_speed = std::min(FLAGS_still_obstacle_speed_threshold, ds0);
// double ds1 = std::max(min_end_speed, ds0 + dds0 * time_to_end_state);
double ds1 = lon_end_vt.first;
double dds1 = 0.0;
double p = lon_end_vt.second; // time to lon end state
// Solve for the coefficients.
coefficients->operator[](0) = s0;
coefficients->operator[](1) = ds0;
coefficients->operator[](2) = 0.5 * dds0;
double b0 = ds1 - dds0 * p - ds0;
double b1 = dds1 - dds0;
double p2 = p * p;
double p3 = p2 * p;
coefficients->operator[](3) = b0 / p2 - b1 / 3.0 / p;
coefficients->operator[](4) = -0.5 / p3 * b0 + 0.25 / p2 * b1;
return true;
}
bool SequencePredictor::GetLateralPolynomial(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double time_to_end_state, std::array<double, 4>* coefficients) {
// Sanity check.
CHECK_NOTNULL(coefficients);
CHECK_GT(obstacle.history_size(), 0U);
CHECK_GT(lane_sequence.lane_segment_size(), 0);
CHECK_GT(lane_sequence.lane_segment(0).lane_point_size(), 0);
// Get obstacle info.
const Feature& feature = obstacle.latest_feature();
double theta = feature.velocity_heading();
double v = feature.speed();
Point3D position = feature.position();
int lane_seg_start_idx = lane_sequence.adc_lane_segment_idx();
int lane_point_start_idx =
lane_sequence.lane_segment(lane_seg_start_idx).adc_lane_point_idx();
if (lane_point_start_idx >=
lane_sequence.lane_segment(lane_seg_start_idx).lane_point_size()) {
lane_point_start_idx =
lane_sequence.lane_segment(lane_seg_start_idx).lane_point_size() - 1;
}
const LanePoint& start_lane_point =
lane_sequence.lane_segment(lane_seg_start_idx)
.lane_point(lane_point_start_idx);
// Get lane info.
double pos_delta_x = position.x() - start_lane_point.position().x();
double pos_delta_y = position.y() - start_lane_point.position().y();
double lane_heading_x = std::cos(start_lane_point.heading());
double lane_heading_y = std::sin(start_lane_point.heading());
// Check if obstacle is to the left(+) or right(-) of the lane.
double cross_prod =
lane_heading_x * pos_delta_y - lane_heading_y * pos_delta_x;
double shift = std::hypot(pos_delta_x, pos_delta_y);
// Set the initial conditions for solving diff. eqn.
double l0 = (cross_prod > 0) ? shift : -shift;
double dl0 = v * std::sin(theta - start_lane_point.heading());
double l1 = 0.0;
double dl1 = 0.0;
// Solve for the coefficients.
coefficients->operator[](0) = l0;
coefficients->operator[](1) = dl0;
double p = time_to_end_state;
double p2 = p * p;
double p3 = p2 * p;
double tmp_var1 = (l1 - dl0) * p;
double tmp_var2 = dl1 - l0 - dl0 * p;
coefficients->operator[](2) = (3.0 * tmp_var2 - tmp_var1) / p2;
coefficients->operator[](3) = (tmp_var1 - 2.0 * tmp_var2) / p3;
return true;
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/sequence/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "sequence_predictor",
srcs = ["sequence_predictor.cc"],
hdrs = ["sequence_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/prediction/container:container_manager",
"//modules/prediction/predictor",
],
)
cc_test(
name = "sequence_predictor_test",
size = "small",
srcs = ["sequence_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/common:prediction_gflags",
"//modules/prediction/evaluator/vehicle:mlp_evaluator",
"//modules/prediction/predictor/sequence:sequence_predictor",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/sequence/sequence_predictor_test.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/mlp_evaluator.h"
namespace apollo {
namespace prediction {
class SequencePredictorTest : public KMLMapBasedTest {
public:
virtual void SetUp() {
const std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
cyber::common::GetProtoFromFile(file, &perception_obstacles_);
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(SequencePredictorTest, General) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator mlp_evaluator;
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
container.BuildLaneGraph();
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
mlp_evaluator.Evaluate(obstacle_ptr, &container);
SequencePredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 0);
LaneSequence* lane_seq = obstacle_ptr->mutable_latest_feature()
->mutable_lane()
->mutable_lane_graph()
->mutable_lane_sequence(0);
std::string sequence_str = predictor.ToString(*lane_seq);
EXPECT_GT(sequence_str.size(), 0);
SequencePredictor::LaneChangeType lane_change_type =
predictor.GetLaneChangeType(lane_seq->mutable_lane_segment(0)->lane_id(),
*lane_seq);
EXPECT_EQ(lane_change_type, SequencePredictor::LaneChangeType::STRAIGHT);
EXPECT_TRUE(predictor.LaneSequenceWithMaxProb(lane_change_type, 0.5, 0.5));
EXPECT_FALSE(predictor.LaneChangeWithMaxProb(lane_change_type, 0.5, 0.5));
Obstacle* ego_vehicle_ptr = container.GetObstacle(FLAGS_ego_vehicle_id);
std::vector<bool> enable_lane_sequence(3, true);
predictor.FilterLaneSequences(*obstacle_ptr->mutable_latest_feature(),
lane_seq->mutable_lane_segment(0)->lane_id(),
ego_vehicle_ptr, &adc_trajectory_container,
&enable_lane_sequence);
EXPECT_TRUE(enable_lane_sequence[0]);
predictor.Clear();
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/sequence/sequence_predictor.h
|
/******************************************************************************
* Copyright 2017 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define the sequence predictor base class
*/
#pragma once
#include <string>
#include <utility>
#include <vector>
#include "gtest/gtest.h"
#include "modules/prediction/predictor/predictor.h"
namespace apollo {
namespace prediction {
class SequencePredictor : public Predictor {
public:
enum class LaneChangeType {
LEFT,
RIGHT,
STRAIGHT,
ONTO_LANE,
INVALID,
};
public:
/**
* @brief Constructor
*/
SequencePredictor() = default;
/**
* @brief Destructor
*/
virtual ~SequencePredictor() = default;
/**
* @brief Make prediction
* @param ADC trajectory container
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
FRIEND_TEST(SequencePredictorTest, General);
protected:
bool GetLongitudinalPolynomial(const Obstacle& obstacle,
const LaneSequence& lane_sequence,
const std::pair<double, double>& lon_end_state,
std::array<double, 5>* coefficients);
bool GetLateralPolynomial(const Obstacle& obstacle,
const LaneSequence& lane_sequence,
const double time_to_end_state,
std::array<double, 4>* coefficients);
/**
* @brief Filter lane sequences
* @param Lane graph
* @param Current lane id
* @param Ego vehicle pointer
* @param ADC trajectory container
* @param Vector of boolean indicating if a lane sequence is disqualified
*/
void FilterLaneSequences(
const Feature& feature, const std::string& lane_id,
const Obstacle* ego_vehicle_ptr,
const ADCTrajectoryContainer* adc_trajectory_container,
std::vector<bool>* enable_lane_sequence);
/**
* @brief Get lane change type
* @param Current lane id
* @param Lane sequence
* @return Integer indicating lane change type:
*/
LaneChangeType GetLaneChangeType(const std::string& lane_id,
const LaneSequence& lane_sequence);
/**
* @brief Get lane change distance with ADC
* @param Target lane sequence
* @param Ego vehicle pointer
* @param ADC trajectory container
* @return Lane change distance with ADC
*/
double GetLaneChangeDistanceWithADC(
const LaneSequence& lane_sequence, const Obstacle* ego_vehicle_ptr,
const ADCTrajectoryContainer* adc_trajectory_container);
/**
* @brief Draw constant acceleration trajectory points
* @param Obstacle
* @param Lane sequence
* @param Total prediction time
* @param Prediction period
* @param acceleration
* @param A vector of generated trajectory points
*/
void DrawConstantAccelerationTrajectory(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double total_time, const double period, const double acceleration,
std::vector<apollo::common::TrajectoryPoint>* points);
/**
* @brief Get lane sequence curvature by s
* @param lane sequence
* @param s
* @return the curvature
*/
double GetLaneSequenceCurvatureByS(const LaneSequence& lane_sequence,
const double s);
/**
* @brief Clear private members
*/
void Clear();
/**
* @brief Convert a lane sequence to string
* @param Lane sequence
* @return String describing the lane sequence
*/
std::string ToString(const LaneSequence& sequence);
private:
/**
* @brief Pick the lane sequence with highest probability
* STRAIGHT lane sequence precedes LEFT/RIGHT lane sequences
* @param Lane change type
* @param Lane sequence probability
* @param Hightest probability
* @return Boolean if the lane sequence is enabled
*/
bool LaneSequenceWithMaxProb(const LaneChangeType& type,
const double probability, const double max_prob);
/**
* @brief Pick the lane change sequence with highest probability
* STRAIGHT lane sequence precedes LEFT/RIGHT lane sequences
* @param Lane change type
* @param Lane sequence probability
* @param Hightest probability
* @return Boolean if the lane sequence is enabled
*/
bool LaneChangeWithMaxProb(const LaneChangeType& type,
const double probability, const double max_prob);
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/interaction/interaction_predictor.h
|
/******************************************************************************
* Copyright 2019 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
*implied. See the License for the specific language governing
*permissions and limitations under the License.
*****************************************************************************/
/**
* @file
* @brief Define interaction predictor
*/
#pragma once
#include <utility>
#include <vector>
#include "modules/prediction/predictor/sequence/sequence_predictor.h"
namespace apollo {
namespace prediction {
class InteractionPredictor : public SequencePredictor {
public:
/**
* @brief Constructor
*/
InteractionPredictor();
/**
* @brief Destructor
*/
virtual ~InteractionPredictor() = default;
/**
* @brief Make prediction
* @param Obstacle pointer
* @param Obstacles container
* @return If predicted successfully
*/
bool Predict(const ADCTrajectoryContainer* adc_trajectory_container,
Obstacle* obstacle,
ObstaclesContainer* obstacles_container) override;
private:
void Clear();
void BuildADCTrajectory(
const ADCTrajectoryContainer* adc_trajectory_container,
const double time_resolution);
bool DrawTrajectory(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double lon_acceleration, const double total_time,
const double period,
std::vector<apollo::common::TrajectoryPoint>* trajectory_points);
double ComputeTrajectoryCost(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double acceleration,
const ADCTrajectoryContainer* adc_trajectory_container);
double LongitudinalAccelerationCost(const double acceleration);
double CentripetalAccelerationCost(const LaneSequence& lane_sequence,
const double speed,
const double acceleration);
double CollisionWithEgoVehicleCost(const LaneSequence& lane_sequence,
const double speed,
const double acceleration);
bool LowerRightOfWayThanEgo(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const ADCTrajectoryContainer* adc_trajectory_container);
double ComputeLikelihood(const double cost);
double ComputePosterior(const double prior, const double likelihood);
private:
std::vector<apollo::common::TrajectoryPoint> adc_trajectory_;
};
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/interaction/interaction_predictor_test.cc
|
/******************************************************************************
* Copyright 2019 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/interaction/interaction_predictor.h"
#include "cyber/common/file.h"
#include "modules/prediction/common/kml_map_based_test.h"
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/vehicle/mlp_evaluator.h"
namespace apollo {
namespace prediction {
class InteractionPredictorTest : public KMLMapBasedTest {
public:
virtual void SetUp() {
const std::string file =
"modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
cyber::common::GetProtoFromFile(file, &perception_obstacles_);
}
protected:
apollo::perception::PerceptionObstacles perception_obstacles_;
};
TEST_F(InteractionPredictorTest, OnLaneCase) {
EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
1501183430.161906);
apollo::perception::PerceptionObstacle perception_obstacle =
perception_obstacles_.perception_obstacle(0);
EXPECT_EQ(perception_obstacle.id(), 1);
MLPEvaluator mlp_evaluator;
ObstaclesContainer container;
ADCTrajectoryContainer adc_trajectory_container;
container.Insert(perception_obstacles_);
container.BuildLaneGraph();
Obstacle* obstacle_ptr = container.GetObstacle(1);
EXPECT_NE(obstacle_ptr, nullptr);
mlp_evaluator.Evaluate(obstacle_ptr, &container);
InteractionPredictor predictor;
predictor.Predict(&adc_trajectory_container, obstacle_ptr, &container);
EXPECT_EQ(predictor.NumOfTrajectories(*obstacle_ptr), 1);
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/interaction/interaction_predictor.cc
|
/******************************************************************************
* Copyright 2019 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/prediction/predictor/interaction/interaction_predictor.h"
#include <algorithm>
#include <limits>
#include <memory>
#include <string>
#include "modules/common/adapters/proto/adapter_config.pb.h"
#include "modules/prediction/common/feature_output.h"
#include "modules/prediction/common/prediction_constants.h"
#include "modules/prediction/common/prediction_gflags.h"
#include "modules/prediction/common/prediction_system_gflags.h"
#include "modules/prediction/common/prediction_util.h"
#include "modules/prediction/container/adc_trajectory/adc_trajectory_container.h"
#include "modules/prediction/container/container_manager.h"
namespace apollo {
namespace prediction {
using apollo::common::PathPoint;
using apollo::common::TrajectoryPoint;
using apollo::hdmap::LaneInfo;
using apollo::prediction::math_util::GetSByConstantAcceleration;
InteractionPredictor::InteractionPredictor() {
predictor_type_ = ObstacleConf::INTERACTION_PREDICTOR;
}
bool InteractionPredictor::Predict(
const ADCTrajectoryContainer* adc_trajectory_container, Obstacle* obstacle,
ObstaclesContainer* obstacles_container) {
Clear();
CHECK_NOTNULL(obstacle);
CHECK_GT(obstacle->history_size(), 0U);
BuildADCTrajectory(adc_trajectory_container,
FLAGS_collision_cost_time_resolution);
obstacle->SetPredictorType(predictor_type_);
Feature* feature_ptr = obstacle->mutable_latest_feature();
if (!feature_ptr->lane().has_lane_graph()) {
AERROR << "Obstacle [" << obstacle->id() << "] has no lane graph.";
return false;
}
auto* lane_graph = feature_ptr->mutable_lane()->mutable_lane_graph();
int num_lane_sequence = lane_graph->lane_sequence_size();
std::vector<double> best_lon_accelerations(num_lane_sequence, 0.0);
std::vector<double> candidate_lon_accelerations = {0.0, -0.5, -1.0, -1.5,
-2.0, -2.5, -3.0};
double smallest_cost = std::numeric_limits<double>::max();
std::vector<double> posteriors(num_lane_sequence, 0.0);
double posterior_sum = 0.0;
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& lane_sequence = lane_graph->lane_sequence(i);
for (const double lon_acceleration : candidate_lon_accelerations) {
double cost = ComputeTrajectoryCost(
*obstacle, lane_sequence, lon_acceleration, adc_trajectory_container);
if (cost < smallest_cost) {
smallest_cost = cost;
best_lon_accelerations[i] = lon_acceleration;
}
}
double likelihood = ComputeLikelihood(smallest_cost);
double prior = lane_sequence.probability();
double posterior = ComputePosterior(prior, likelihood);
posteriors[i] = posterior;
posterior_sum += posterior;
}
int best_seq_idx = 0;
double largest_posterior = 0.0;
CHECK_EQ(posteriors.size(),
static_cast<size_t>(lane_graph->lane_sequence_size()));
for (int i = 0; i < num_lane_sequence; ++i) {
double normalized_posterior =
posteriors[i] / (posterior_sum + FLAGS_double_precision);
lane_graph->mutable_lane_sequence(i)->set_probability(normalized_posterior);
if (normalized_posterior > largest_posterior) {
largest_posterior = normalized_posterior;
best_seq_idx = i;
}
}
double probability_threshold = 0.5;
if (largest_posterior > probability_threshold) {
for (int i = 0; i < num_lane_sequence; ++i) {
const LaneSequence& lane_sequence = lane_graph->lane_sequence(i);
if (lane_sequence.probability() < probability_threshold) {
continue;
}
double best_lon_acceleration = best_lon_accelerations[i];
if (lane_sequence.has_stop_sign()) {
double stop_acceleration = 0.0;
double stop_distance = lane_sequence.stop_sign().lane_sequence_s() -
lane_sequence.lane_s();
SupposedToStop(*feature_ptr, stop_distance, &stop_acceleration);
best_lon_acceleration =
std::min(best_lon_acceleration, stop_acceleration);
}
std::vector<TrajectoryPoint> points;
DrawTrajectory(*obstacle, lane_sequence, best_lon_acceleration,
FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, &points);
Trajectory trajectory = GenerateTrajectory(points);
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
}
} else {
const LaneSequence& sequence = lane_graph->lane_sequence(best_seq_idx);
double best_lon_acceleration = best_lon_accelerations[best_seq_idx];
if (sequence.has_stop_sign()) {
double stop_distance =
sequence.stop_sign().lane_sequence_s() - sequence.lane_s();
SupposedToStop(*feature_ptr, stop_distance, &best_lon_acceleration);
}
std::vector<TrajectoryPoint> points;
DrawTrajectory(*obstacle, lane_graph->lane_sequence(best_seq_idx),
best_lon_acceleration,
FLAGS_prediction_trajectory_time_length,
FLAGS_prediction_trajectory_time_resolution, &points);
Trajectory trajectory = GenerateTrajectory(points);
obstacle->mutable_latest_feature()->add_predicted_trajectory()->CopyFrom(
trajectory);
}
return true;
}
void InteractionPredictor::Clear() { Predictor::Clear(); }
void InteractionPredictor::BuildADCTrajectory(
const ADCTrajectoryContainer* adc_trajectory_container,
const double time_resolution) {
if (adc_trajectory_container == nullptr) {
AERROR << "Null adc trajectory container";
return;
}
const auto& adc_trajectory = adc_trajectory_container->adc_trajectory();
double curr_timestamp = 0.0;
for (const TrajectoryPoint& point : adc_trajectory.trajectory_point()) {
if (point.relative_time() + FLAGS_double_precision > curr_timestamp) {
adc_trajectory_.push_back(point);
curr_timestamp += time_resolution;
}
}
}
bool InteractionPredictor::DrawTrajectory(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double lon_acceleration, const double total_time, const double period,
std::vector<TrajectoryPoint>* trajectory_points) {
// Sanity check.
CHECK_NOTNULL(trajectory_points);
trajectory_points->clear();
const Feature& feature = obstacle.latest_feature();
if (!feature.has_position() || !feature.has_velocity() ||
!feature.position().has_x() || !feature.position().has_y()) {
AERROR << "Obstacle [" << obstacle.id()
<< " is missing position or velocity";
return false;
}
Eigen::Vector2d position(feature.position().x(), feature.position().y());
double speed = feature.speed();
int lane_segment_index = 0;
std::string lane_id =
lane_sequence.lane_segment(lane_segment_index).lane_id();
std::shared_ptr<const LaneInfo> lane_info = PredictionMap::LaneById(lane_id);
double lane_s = 0.0;
double lane_l = 0.0;
if (!PredictionMap::GetProjection(position, lane_info, &lane_s, &lane_l)) {
AERROR << "Failed in getting lane s and lane l";
return false;
}
double approach_rate = FLAGS_go_approach_rate;
if (!lane_sequence.vehicle_on_lane()) {
approach_rate = FLAGS_cutin_approach_rate;
}
size_t total_num = static_cast<size_t>(total_time / period);
for (size_t i = 0; i < total_num; ++i) {
double relative_time = static_cast<double>(i) * period;
Eigen::Vector2d point;
double theta = M_PI;
if (!PredictionMap::SmoothPointFromLane(lane_id, lane_s, lane_l, &point,
&theta)) {
AERROR << "Unable to get smooth point from lane [" << lane_id
<< "] with s [" << lane_s << "] and l [" << lane_l << "]";
break;
}
TrajectoryPoint trajectory_point;
PathPoint path_point;
path_point.set_x(point.x());
path_point.set_y(point.y());
path_point.set_z(0.0);
path_point.set_theta(theta);
path_point.set_lane_id(lane_id);
trajectory_point.mutable_path_point()->CopyFrom(path_point);
trajectory_point.set_v(speed);
trajectory_point.set_a(lon_acceleration);
trajectory_point.set_relative_time(relative_time);
trajectory_points->emplace_back(std::move(trajectory_point));
lane_s += std::max(
0.0, speed * period + 0.5 * lon_acceleration * period * period);
speed += lon_acceleration * period;
while (lane_s > PredictionMap::LaneById(lane_id)->total_length() &&
lane_segment_index + 1 < lane_sequence.lane_segment_size()) {
lane_segment_index += 1;
lane_s = lane_s - PredictionMap::LaneById(lane_id)->total_length();
lane_id = lane_sequence.lane_segment(lane_segment_index).lane_id();
}
lane_l *= approach_rate;
}
return true;
}
double InteractionPredictor::ComputeTrajectoryCost(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const double acceleration,
const ADCTrajectoryContainer* adc_trajectory_container) {
CHECK_GT(obstacle.history_size(), 0U);
double speed = obstacle.latest_feature().speed();
double total_cost = 0.0;
double lon_acc_cost = LongitudinalAccelerationCost(acceleration);
total_cost += FLAGS_longitudinal_acceleration_cost_weight * lon_acc_cost;
double centri_acc_cost =
CentripetalAccelerationCost(lane_sequence, speed, acceleration);
total_cost += FLAGS_centripedal_acceleration_cost_weight * centri_acc_cost;
double collision_cost = 0.0;
if (LowerRightOfWayThanEgo(obstacle, lane_sequence,
adc_trajectory_container)) {
collision_cost =
CollisionWithEgoVehicleCost(lane_sequence, speed, acceleration);
}
total_cost += FLAGS_collision_cost_weight * collision_cost;
if (FLAGS_prediction_offline_mode ==
PredictionConstants::kDumpDataForTuning) {
std::vector<double> cost_values = {lon_acc_cost, centri_acc_cost,
collision_cost};
FeatureOutput::InsertDataForTuning(obstacle.latest_feature(), cost_values,
"interaction", lane_sequence,
adc_trajectory_);
}
return total_cost;
}
double InteractionPredictor::LongitudinalAccelerationCost(
const double acceleration) {
return acceleration * acceleration;
}
double InteractionPredictor::CentripetalAccelerationCost(
const LaneSequence& lane_sequence, const double speed,
const double acceleration) {
double cost_abs_sum = 0.0;
double cost_sqr_sum = 0.0;
double curr_time = 0.0;
while (curr_time < FLAGS_prediction_trajectory_time_length) {
double s = GetSByConstantAcceleration(speed, acceleration, curr_time);
double v = std::max(0.0, speed + acceleration * curr_time);
double kappa = GetLaneSequenceCurvatureByS(lane_sequence, s);
double centri_acc = v * v * kappa;
cost_abs_sum += std::abs(centri_acc);
cost_sqr_sum += centri_acc * centri_acc;
curr_time += FLAGS_collision_cost_time_resolution;
}
return cost_sqr_sum / (cost_abs_sum + FLAGS_double_precision);
}
double InteractionPredictor::CollisionWithEgoVehicleCost(
const LaneSequence& lane_sequence, const double speed,
const double acceleration) {
CHECK_GT(lane_sequence.lane_segment_size(), 0);
double cost_abs_sum = 0.0;
double cost_sqr_sum = 0.0;
int num_lane_segment = lane_sequence.lane_segment_size();
double remained_s = lane_sequence.lane_segment(0).start_s();
int lane_seg_idx = 0;
double prev_s = 0.0;
for (const TrajectoryPoint& adc_trajectory_point : adc_trajectory_) {
double relative_time = adc_trajectory_point.relative_time();
double curr_s =
GetSByConstantAcceleration(speed, acceleration, relative_time);
double delta_s = curr_s - prev_s;
remained_s += delta_s;
while (lane_seg_idx < num_lane_segment) {
const LaneSegment& lane_segment =
lane_sequence.lane_segment(lane_seg_idx);
const std::string& lane_id = lane_segment.lane_id();
std::shared_ptr<const LaneInfo> lane_info_ptr =
PredictionMap::LaneById(lane_id);
if (lane_info_ptr == nullptr) {
AERROR << "Null lane info ptr found with lane ID [" << lane_id << "]";
continue;
}
double lane_length = lane_info_ptr->total_length();
if (remained_s < lane_length) {
apollo::common::PointENU point_enu =
lane_info_ptr->GetSmoothPoint(remained_s);
double obs_x = point_enu.x();
double obs_y = point_enu.y();
double adc_x = adc_trajectory_point.path_point().x();
double adc_y = adc_trajectory_point.path_point().y();
double distance = std::hypot(adc_x - obs_x, adc_y - obs_y);
double cost = std::exp(-FLAGS_collision_cost_exp_coefficient *
distance * distance);
cost_abs_sum += std::abs(cost);
cost_sqr_sum += cost * cost;
break;
} else {
++lane_seg_idx;
remained_s -= lane_length;
}
}
// Out of the while loop
prev_s = curr_s;
}
return cost_sqr_sum / (cost_abs_sum + FLAGS_double_precision);
}
bool InteractionPredictor::LowerRightOfWayThanEgo(
const Obstacle& obstacle, const LaneSequence& lane_sequence,
const ADCTrajectoryContainer* adc_trajectory_container) {
if (adc_trajectory_container != nullptr &&
adc_trajectory_container->IsProtected()) {
return true;
}
return lane_sequence.right_of_way() < 0;
}
double InteractionPredictor::ComputeLikelihood(const double cost) {
double alpha = FLAGS_likelihood_exp_coefficient;
return std::exp(-alpha * cost);
}
double InteractionPredictor::ComputePosterior(const double prior,
const double likelihood) {
return prior * likelihood;
}
} // namespace prediction
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/prediction/predictor
|
apollo_public_repos/apollo/modules/prediction/predictor/interaction/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library", "cc_test")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "interaction_predictor",
srcs = ["interaction_predictor.cc"],
hdrs = ["interaction_predictor.h"],
copts = [
"-DMODULE_NAME=\\\"prediction\\\"",
],
deps = [
"//modules/common/adapters/proto:adapter_config_cc_proto",
"//modules/prediction/common:feature_output",
"//modules/prediction/common:prediction_util",
"//modules/prediction/predictor/sequence:sequence_predictor",
],
)
cc_test(
name = "interaction_predictor_test",
size = "small",
srcs = ["interaction_predictor_test.cc"],
data = [
"//modules/prediction:prediction_data",
"//modules/prediction:prediction_testdata",
],
deps = [
"//modules/prediction/common:kml_map_based_test",
"//modules/prediction/evaluator/vehicle:mlp_evaluator",
"//modules/prediction/predictor/interaction:interaction_predictor",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/conf/prediction_navi_conf.pb.txt
|
topic_conf {
adccontainer_topic_name: "/apollo/prediction/adccontainer"
container_topic_name: "/apollo/prediction/container"
evaluator_topic_name: "/apollo/prediction/evaluator"
localization_topic: "/apollo/localization/pose"
perception_obstacle_topic: "/apollo/perception/obstacles"
perception_obstacles_topic_name: "/apollo/prediction/perception_obstacles"
planning_trajectory_topic: "/apollo/planning"
prediction_topic: "/apollo/prediction"
storytelling_topic: "/apollo/storytelling"
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: ON_LANE
evaluator_type: COST_EVALUATOR
predictor_type: SINGLE_LANE_PREDICTOR
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: OFF_LANE
predictor_type: EMPTY_PREDICTOR
}
obstacle_conf {
obstacle_type: PEDESTRIAN
predictor_type: FREE_MOVE_PREDICTOR
}
obstacle_conf {
obstacle_type: BICYCLE
obstacle_status: ON_LANE
evaluator_type: COST_EVALUATOR
predictor_type: SINGLE_LANE_PREDICTOR
}
obstacle_conf {
obstacle_type: BICYCLE
obstacle_status: OFF_LANE
predictor_type: EMPTY_PREDICTOR
}
obstacle_conf {
obstacle_type: UNKNOWN
obstacle_status: ON_LANE
evaluator_type: COST_EVALUATOR
predictor_type: SINGLE_LANE_PREDICTOR
}
obstacle_conf {
obstacle_type: UNKNOWN
obstacle_status: OFF_LANE
predictor_type: EMPTY_PREDICTOR
}
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/conf/adapter.conf
|
config {
type: PERCEPTION_OBSTACLES
mode: RECEIVE_ONLY
message_history_limit: 1
}
config {
type: LOCALIZATION
mode: RECEIVE_ONLY
message_history_limit: 10
}
config {
type: PLANNING_TRAJECTORY
mode: RECEIVE_ONLY
message_history_limit: 1
}
config {
type: RELATIVE_MAP
mode: RECEIVE_ONLY
message_history_limit: 1
}
config {
type: STORYTELLING
mode: RECEIVE_ONLY
message_history_limit: 1
}
config {
type: PREDICTION
mode: PUBLISH_ONLY
message_history_limit: 10
}
is_ros: true
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/conf/prediction_navi.conf
|
--flagfile=modules/prediction/conf/prediction.conf
--prediction_conf_file=modules/prediction/conf/prediction_navi_conf.pb.txt
--adjust_velocity_by_obstacle_heading
--lane_search_radius=5.0
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/conf/prediction_conf.pb.txt
|
topic_conf {
adccontainer_topic_name: "/apollo/prediction/adccontainer"
container_topic_name: "/apollo/prediction/container"
evaluator_topic_name: "/apollo/prediction/evaluator"
localization_topic: "/apollo/localization/pose"
perception_obstacle_topic: "/apollo/perception/obstacles"
perception_obstacles_topic_name: "/apollo/prediction/perception_obstacles"
planning_trajectory_topic: "/apollo/planning"
prediction_topic: "/apollo/prediction"
storytelling_topic: "/apollo/storytelling"
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: ON_LANE
priority_type: CAUTION
evaluator_type: VECTORNET_EVALUATOR
predictor_type: EXTRAPOLATION_PREDICTOR
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: ON_LANE
priority_type: NORMAL
evaluator_type: CRUISE_MLP_EVALUATOR
predictor_type: MOVE_SEQUENCE_PREDICTOR
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: IN_JUNCTION
priority_type: CAUTION
evaluator_type: VECTORNET_EVALUATOR
predictor_type: EXTRAPOLATION_PREDICTOR
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: IN_JUNCTION
priority_type: NORMAL
evaluator_type: JUNCTION_MLP_EVALUATOR
predictor_type: LANE_SEQUENCE_PREDICTOR
}
obstacle_conf {
obstacle_type: VEHICLE
obstacle_status: OFF_LANE
predictor_type: FREE_MOVE_PREDICTOR
}
obstacle_conf {
obstacle_type: PEDESTRIAN
obstacle_status: MOVING
evaluator_type: SEMANTIC_LSTM_EVALUATOR
predictor_type: FREE_MOVE_PREDICTOR
}
obstacle_conf {
obstacle_type: BICYCLE
obstacle_status: ON_LANE
evaluator_type: CYCLIST_KEEP_LANE_EVALUATOR
predictor_type: LANE_SEQUENCE_PREDICTOR
}
obstacle_conf {
obstacle_type: BICYCLE
obstacle_status: OFF_LANE
predictor_type: FREE_MOVE_PREDICTOR
}
obstacle_conf {
obstacle_type: UNKNOWN
obstacle_status: ON_LANE
evaluator_type: MLP_EVALUATOR
predictor_type: LANE_SEQUENCE_PREDICTOR
}
obstacle_conf {
obstacle_type: UNKNOWN
obstacle_status: OFF_LANE
predictor_type: FREE_MOVE_PREDICTOR
}
obstacle_conf {
obstacle_type: VEHICLE
interactive_tag: INTERACTION
evaluator_type: JOINTLY_PREDICTION_PLANNING_EVALUATOR
predictor_type: EXTRAPOLATION_PREDICTOR
}
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/conf/offline_prediction.conf
|
--flagfile=/apollo/modules/common/data/global_flagfile.txt
--prediction_conf_file=/apollo/modules/prediction/conf/prediction_conf.pb.txt
--noadjust_velocity_by_obstacle_heading
--noadjust_velocity_by_position_shift
--noenable_kf_tracking
--noprediction_offline_mode
--lane_change_dist=10.0
--lane_search_radius=5.0
--lane_sequence_threshold_junction=0.3
--prediction_offline_mode=true
--junction_distance_threshold=30.0
--noenable_prioritize_obstacles
| 0
|
apollo_public_repos/apollo/modules/prediction
|
apollo_public_repos/apollo/modules/prediction/conf/prediction.conf
|
--flagfile=/apollo/modules/common/data/global_flagfile.txt
--prediction_conf_file=/apollo/modules/prediction/conf/prediction_conf.pb.txt
--noadjust_velocity_by_obstacle_heading
--noadjust_velocity_by_position_shift
--noenable_kf_tracking
--prediction_offline_mode=0
--lane_change_dist=10.0
--lane_search_radius=5.0
--lane_sequence_threshold_junction=0.3
--enable_multi_thread
--max_thread_num=8
--max_caution_thread_num=4
--slow_obstacle_speed_threshold=3.1
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/cycle_routing_manager.cc
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/task_manager/cycle_routing_manager.h"
#include "modules/task_manager/common/task_manager_gflags.h"
namespace apollo {
namespace task_manager {
bool CheckPointDistanceInThreshold(common::PointENU point_a,
common::PointENU point_b, double distance) {
double x_dis = point_a.x() - point_b.x();
double y_dis = point_a.y() - point_b.y();
return x_dis * x_dis + y_dis * y_dis < distance * distance;
}
common::Status CycleRoutingManager::Init(
const CycleRoutingTask& cycle_routing_task) {
cycle_ = cycle_routing_task.cycle_num();
auto waypoints = cycle_routing_task.routing_request().waypoint();
waypoint_num_ = waypoints.size();
begin_point_ = waypoints[0];
end_point_ = waypoints[waypoint_num_ - 1];
is_allowed_to_route_ = true;
original_routing_request_ = cycle_routing_task.routing_request();
map_service_.reset(new apollo::dreamview::MapService());
AINFO << "New cycle routing task: cycle " << cycle_ << ", begin point "
<< begin_point_.pose().x() << " " << begin_point_.pose().y()
<< ", end point " << end_point_.pose().x() << " "
<< end_point_.pose().y();
return common::Status::OK();
}
bool CycleRoutingManager::GetNewRouting(
const localization::Pose& pose,
routing::RoutingRequest* new_routing_request) {
AINFO << "GetNewRouting: localization_pose: " << pose.position().x() << " "
<< pose.position().y() << ", begin point " << begin_point_.pose().x()
<< " " << begin_point_.pose().y() << ", end point "
<< end_point_.pose().x() << " " << end_point_.pose().y()
<< ", threshold " << FLAGS_threshold_for_destination_check
<< ", allowed_to_send_routing_request " << is_allowed_to_route_;
if (is_allowed_to_route_) {
if (CheckPointDistanceInThreshold(begin_point_.pose(), pose.position(),
FLAGS_threshold_for_destination_check)) {
AINFO << "GetNewRouting: reach begin point."
<< "Remaining cycles: " << cycle_;
new_routing_request->CopyFrom(original_routing_request_);
auto cur_point = new_routing_request->mutable_waypoint(0);
if (!map_service_->ConstructLaneWayPointWithHeading(
pose.position().x(), pose.position().y(), pose.heading(),
cur_point)) {
AINFO << "GetNewRouting: construct begin lane way point fail!";
return false;
}
is_allowed_to_route_ = false;
return true;
}
} else {
if (CheckPointDistanceInThreshold(end_point_.pose(), pose.position(),
FLAGS_threshold_for_destination_check)) {
AINFO << "GetNewRouting: reach end point. "
<< "Remaining cycles: " << cycle_;
new_routing_request->clear_waypoint();
auto cur_point = new_routing_request->add_waypoint();
if (!map_service_->ConstructLaneWayPointWithHeading(
pose.position().x(), pose.position().y(), pose.heading(),
cur_point)) {
AINFO << "GetNewRouting: construct end lane way point fail!";
return false;
}
auto next_point = new_routing_request->add_waypoint();
next_point->CopyFrom(begin_point_);
--cycle_;
is_allowed_to_route_ = true;
return true;
}
}
return false;
}
} // namespace task_manager
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/task_manager_component.h
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include <string>
#include "cyber/class_loader/class_loader.h"
#include "cyber/component/component.h"
#include "modules/common_msgs/planning_msgs/planning.pb.h"
#include "modules/task_manager/cycle_routing_manager.h"
#include "modules/task_manager/parking_routing_manager.h"
namespace apollo {
namespace task_manager {
using apollo::localization::LocalizationEstimate;
class TaskManagerComponent final : public cyber::Component<task_manager::Task> {
public:
TaskManagerComponent() = default;
~TaskManagerComponent() = default;
public:
bool Init() override;
bool Proc(const std::shared_ptr<task_manager::Task>& task) override;
private:
std::shared_ptr<cyber::Reader<LocalizationEstimate>> localization_reader_;
std::shared_ptr<cyber::Reader<routing::RoutingResponse>> response_reader_;
std::shared_ptr<cyber::Reader<planning::ADCTrajectory>> trajectory_reader_;
std::shared_ptr<cyber::Writer<routing::RoutingRequest>> request_writer_;
std::shared_ptr<CycleRoutingManager> cycle_routing_manager_;
std::shared_ptr<ParkingRoutingManager> parking_routing_manager_;
routing::RoutingRequest routing_request_;
routing::RoutingResponse routing_response_;
LocalizationEstimate localization_;
apollo::planning::ADCTrajectory planning_;
std::mutex mutex_;
std::string task_name_;
};
CYBER_REGISTER_COMPONENT(TaskManagerComponent)
} // namespace task_manager
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/parking_routing_manager.cc
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/task_manager/parking_routing_manager.h"
#include "modules/common/configs/vehicle_config_helper.h"
#include "modules/common/math/math_utils.h"
#include "modules/map/hdmap/hdmap.h"
#include "modules/map/hdmap/hdmap_common.h"
#include "modules/map/hdmap/hdmap_util.h"
#include "modules/task_manager/common/task_manager_gflags.h"
namespace apollo {
namespace task_manager {
using apollo::common::PointENU;
using apollo::common::math::Vec2d;
using apollo::hdmap::ParkingSpaceInfoConstPtr;
using apollo::routing::ParkingSpaceType;
ParkingRoutingManager::ParkingRoutingManager()
: monitor_logger_buffer_(
apollo::common::monitor::MonitorMessageItem::TASK_MANAGER) {}
common::Status ParkingRoutingManager::Init(
const ParkingRoutingTask& parking_routing_task) {
return common::Status::OK();
}
bool ParkingRoutingManager::ConstructParkingRoutingRequest(
ParkingRoutingTask* parking_routing_task) {
auto hdmap_ = hdmap::HDMapUtil::BaseMapPtr();
hdmap::Id id;
id.set_id(parking_routing_task->routing_request()
.parking_info()
.parking_space_id());
auto parking_space_info = hdmap_->GetParkingSpaceById(id);
auto request_parking_info =
parking_routing_task->mutable_routing_request()->mutable_parking_info();
if (parking_space_info == nullptr) {
AERROR << "Can not find parking space" << id_ << "in map";
return false;
}
auto points = parking_space_info->polygon().points();
// 0 1 2 3: left_top right_top right_rear left_rear corner point for heading
// upward
Vec2d center_point(0, 0);
for (size_t i = 0; i < points.size(); i++) {
center_point += points[i];
}
center_point /= 4.0;
request_parking_info->mutable_parking_point()->set_x(center_point.x());
request_parking_info->mutable_parking_point()->set_y(center_point.y());
request_parking_info->mutable_parking_point()->set_z(0);
apollo::common::PointENU center_enu;
center_enu.set_x(center_point.x());
center_enu.set_y(center_point.y());
apollo::hdmap::LaneInfoConstPtr nearest_lane;
double nearest_s;
double nearest_l;
hdmap_->GetNearestLane(center_enu, &nearest_lane, &nearest_s, &nearest_l);
double lane_heading = nearest_lane->Heading(nearest_s);
double diff_angle = common::math::AngleDiff(
lane_heading, parking_space_info->parking_space().heading());
if (std::fabs(diff_angle) < M_PI / 3.0) {
AINFO << "Find a parallel parking" << id_ << "lane_heading" << lane_heading
<< "parking heading" << parking_space_info->parking_space().heading();
request_parking_info->set_parking_space_type(
ParkingSpaceType::PARALLEL_PARKING);
auto left_down = request_parking_info->mutable_corner_point()->add_point();
left_down->set_x(points[0].x());
left_down->set_y(points[0].y());
auto right_down = request_parking_info->mutable_corner_point()->add_point();
right_down->set_x(points[1].x());
right_down->set_y(points[1].y());
auto right_up = request_parking_info->mutable_corner_point()->add_point();
right_up->set_x(points[2].x());
right_up->set_y(points[2].y());
auto left_up = request_parking_info->mutable_corner_point()->add_point();
left_up->set_x(points[3].x());
left_up->set_y(points[3].y());
} else {
AINFO << "Find a vertical parking";
request_parking_info->set_parking_space_type(
ParkingSpaceType::VERTICAL_PLOT);
auto left_down = request_parking_info->mutable_corner_point()->add_point();
left_down->set_x(points[0].x());
left_down->set_y(points[0].y());
auto right_down = request_parking_info->mutable_corner_point()->add_point();
right_down->set_x(points[1].x());
right_down->set_y(points[1].y());
auto right_up = request_parking_info->mutable_corner_point()->add_point();
right_up->set_x(points[2].x());
right_up->set_y(points[2].y());
auto left_up = request_parking_info->mutable_corner_point()->add_point();
left_up->set_x(points[3].x());
left_up->set_y(points[3].y());
}
// extend last point to aviod referenceline generated failed in parking
auto last_waypoint = parking_routing_task->mutable_routing_request()
->mutable_waypoint()
->rbegin();
static constexpr double kExtendParkingLength = 20;
apollo::common::PointENU extend_point;
extend_point.set_x(last_waypoint->pose().x() +
kExtendParkingLength * std::cos(lane_heading));
extend_point.set_y(last_waypoint->pose().y() +
kExtendParkingLength * std::sin(lane_heading));
hdmap_->GetNearestLaneWithHeading(extend_point, 20, lane_heading, M_PI_2,
&nearest_lane, &nearest_s, &nearest_l);
extend_point = nearest_lane->GetSmoothPoint(nearest_s);
last_waypoint->mutable_pose()->set_x(extend_point.x());
last_waypoint->mutable_pose()->set_y(extend_point.y());
last_waypoint->set_id(nearest_lane->id().id());
last_waypoint->set_s(nearest_s);
return true;
}
} // namespace task_manager
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/parking_routing_manager.h
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include <string>
#include <vector>
#include "modules/common_msgs/localization_msgs/localization.pb.h"
#include "modules/common_msgs/task_manager_msgs/task_manager.pb.h"
#include "modules/task_manager/proto/task_manager_config.pb.h"
#include "modules/common/monitor_log/monitor_log_buffer.h"
#include "modules/common/status/status.h"
namespace apollo {
namespace task_manager {
class ParkingRoutingManager {
public:
ParkingRoutingManager();
/**
* @brief module initialization function
* @return initialization status
*/
common::Status Init(
const task_manager::ParkingRoutingTask& parking_routing_task);
bool ConstructParkingRoutingRequest(ParkingRoutingTask* parking_routing_task);
/**
* @brief destructor
*/
virtual ~ParkingRoutingManager() = default;
private:
bool has_space_ = false;
bool has_space_id_ = false;
std::string id_ = "";
apollo::common::monitor::MonitorLogBuffer monitor_logger_buffer_;
};
} // namespace task_manager
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/cyberfile.xml
|
<package format="2">
<name>task-manager</name>
<version>local</version>
<description>
Apollo task_manager module.
</description>
<maintainer email="apollo-support@baidu.com">Apollo</maintainer>
<license>Apache License 2.0</license>
<url type="website">https://www.apollo.auto/</url>
<url type="repository">https://github.com/ApolloAuto/apollo</url>
<url type="bugtracker">https://github.com/ApolloAuto/apollo/issues</url>
<type>module</type>
<depend repo_name="common-msgs" lib_names="common-msgs">common-msgs-dev</depend>
<depend type="binary" repo_name="common" lib_names="common">common-dev</depend>
<depend type="binary" repo_name="dreamview" lib_names="dreamview">dreamview-dev</depend>
<depend repo_name="com_github_gflags_gflags" lib_names="gflags">3rd-gflags-dev</depend>
<depend lib_names="protobuf" repo_name="com_google_protobuf">3rd-protobuf-dev</depend>
<depend expose="False">3rd-rules-proto-dev</depend>
<src_path url="https://github.com/ApolloAuto/apollo">//modules/task_manager</src_path>
</package>
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/task-manager.BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library")
cc_library(
name = "task-manager",
includes = ["include"],
hdrs = glob(["include/**/*.h"]),
srcs = glob(["lib/**/*.so*"]),
include_prefix = "modules/task_manager",
strip_include_prefix = "include",
visibility = ["//visibility:public"],
)
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_binary", "cc_library")
load("//tools/install:install.bzl", "install", "install_files", "install_src_files")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
TASK_MANAGER_COPTS = ['-DMODULE_NAME=\\"task_manager\\"']
cc_library(
name = "cycle_routing_manager_lib",
srcs = ["cycle_routing_manager.cc"],
hdrs = ["cycle_routing_manager.h"],
copts = TASK_MANAGER_COPTS,
deps = [
"//modules/common/monitor_log",
"//modules/common/status",
"//modules/dreamview/backend/map:map_service",
"//modules/common_msgs/localization_msgs:localization_cc_proto",
"//modules/task_manager/common:task_manager_gflags",
"//modules/common_msgs/task_manager_msgs:task_manager_cc_proto",
],
alwayslink = True,
)
cc_library(
name = "parking_routing_manager_lib",
srcs = ["parking_routing_manager.cc"],
hdrs = ["parking_routing_manager.h"],
copts = TASK_MANAGER_COPTS,
deps = [
"//modules/common/monitor_log",
"//modules/common/status",
"//modules/dreamview/backend/map:map_service",
"//modules/common/configs:vehicle_config_helper",
"//modules/task_manager/common:task_manager_gflags",
"//modules/common_msgs/task_manager_msgs:task_manager_cc_proto",
"//modules/task_manager/proto:task_manager_config_cc_proto",
],
alwayslink = True,
)
cc_library(
name = "task_manager_component_lib",
srcs = ["task_manager_component.cc"],
hdrs = ["task_manager_component.h"],
copts = TASK_MANAGER_COPTS,
deps = [
":cycle_routing_manager_lib",
":parking_routing_manager_lib",
"//cyber",
"//modules/task_manager/proto:task_manager_config_cc_proto",
"//modules/common_msgs/planning_msgs:planning_cc_proto",
],
alwayslink = True,
)
cc_binary(
name = "libtask_manager_component.so",
linkshared = True,
linkstatic = True,
deps = [":task_manager_component_lib"],
)
install(
name = "install",
data_dest = "task-manager",
library_dest = "task-manager/lib",
data = [
":runtime_data",
":cyberfile.xml",
":task-manager.BUILD",
],
targets = [
":libtask_manager_component.so",
],
deps = [
":pb_hdrs",
"//modules/task_manager/proto:py_pb_task_manager"
],
)
install(
name = "pb_hdrs",
data_dest = "task-manager/include",
data = [
"//modules/task_manager/proto:task_manager_config_cc_proto",
],
)
install_src_files(
name = "install_src",
deps = [
":install_task_manager_src",
":install_task_manager_hdrs"
],
)
install_src_files(
name = "install_task_manager_src",
src_dir = ["."],
dest = "task-manager/src",
filter = "*",
)
install_src_files(
name = "install_task_manager_hdrs",
src_dir = ["."],
dest = "task-manager/include",
filter = "*.h",
)
filegroup(
name = "runtime_data",
srcs = glob([
"conf/*.conf",
"conf/*.txt",
"dag/*.dag",
]),
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/cycle_routing_manager.h
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include <string>
#include <vector>
#include "modules/common_msgs/localization_msgs/localization.pb.h"
#include "modules/common_msgs/task_manager_msgs/task_manager.pb.h"
#include "modules/common/monitor_log/monitor_log_buffer.h"
#include "modules/common/status/status.h"
#include "modules/dreamview/backend/map/map_service.h"
namespace apollo {
namespace task_manager {
class CycleRoutingManager {
public:
CycleRoutingManager() = default;
/**
* @brief module initialization function
* @return initialization status
*/
common::Status Init(const task_manager::CycleRoutingTask& cycle_routing_task);
/**
* @brief Get new routing if the vehicle reaches the begin/end point
* @return false/true
*/
bool GetNewRouting(const localization::Pose& pose,
routing::RoutingRequest* routing_request_);
/**
* @brief get remaining cycle number
* @return remaining cycle number
*/
int GetCycle() const { return cycle_; }
/**
* @brief destructor
*/
virtual ~CycleRoutingManager() = default;
private:
int cycle_ = 0;
int waypoint_num_ = 0;
bool is_allowed_to_route_ = false;
routing::LaneWaypoint begin_point_;
routing::LaneWaypoint end_point_;
std::unique_ptr<apollo::dreamview::MapService> map_service_;
routing::RoutingRequest original_routing_request_;
};
} // namespace task_manager
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/task_manager/task_manager_component.cc
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/task_manager/task_manager_component.h"
#include "modules/task_manager/proto/task_manager_config.pb.h"
#include "cyber/time/rate.h"
namespace apollo {
namespace task_manager {
using apollo::cyber::ComponentBase;
using apollo::cyber::Rate;
using apollo::localization::LocalizationEstimate;
using apollo::planning::ADCTrajectory;
using apollo::routing::RoutingRequest;
using apollo::routing::RoutingResponse;
bool TaskManagerComponent::Init() {
TaskManagerConfig task_manager_conf;
ACHECK(cyber::ComponentBase::GetProtoConfig(&task_manager_conf))
<< "Unable to load task_manager conf file: "
<< cyber::ComponentBase::ConfigFilePath();
AINFO << "Config file: " << cyber::ComponentBase::ConfigFilePath()
<< " is loaded.";
localization_reader_ = node_->CreateReader<LocalizationEstimate>(
task_manager_conf.topic_config().localization_pose_topic(),
[this](const std::shared_ptr<LocalizationEstimate>& localization) {
ADEBUG << "Received localization data: run localization callback.";
std::lock_guard<std::mutex> lock(mutex_);
localization_.CopyFrom(*localization);
});
response_reader_ = node_->CreateReader<RoutingResponse>(
task_manager_conf.topic_config().routing_response_topic(),
[this](const std::shared_ptr<RoutingResponse>& response) {
ADEBUG << "Received routing_response data: run response callback.";
std::lock_guard<std::mutex> lock(mutex_);
routing_response_.CopyFrom(*response);
});
cyber::proto::RoleAttributes attr;
attr.set_channel_name(
task_manager_conf.topic_config().routing_request_topic());
auto qos = attr.mutable_qos_profile();
qos->set_history(apollo::cyber::proto::QosHistoryPolicy::HISTORY_KEEP_LAST);
qos->set_reliability(
apollo::cyber::proto::QosReliabilityPolicy::RELIABILITY_RELIABLE);
// Don't send the history message when new readers are found.
qos->set_durability(
apollo::cyber::proto::QosDurabilityPolicy::DURABILITY_SYSTEM_DEFAULT);
request_writer_ = node_->CreateWriter<RoutingRequest>(attr);
return true;
}
bool TaskManagerComponent::Proc(const std::shared_ptr<Task>& task) {
if (task->task_type() != CYCLE_ROUTING &&
task->task_type() != PARKING_ROUTING) {
AERROR << "Task type is not cycle_routing or parking_routing.";
return false;
}
if (task->task_type() == CYCLE_ROUTING) {
cycle_routing_manager_ = std::make_shared<CycleRoutingManager>();
cycle_routing_manager_->Init(task->cycle_routing_task());
routing_request_ = task->cycle_routing_task().routing_request();
Rate rate(1.0);
while (cycle_routing_manager_->GetCycle() > 0) {
if (cycle_routing_manager_->GetNewRouting(localization_.pose(),
&routing_request_)) {
auto last_routing_response_ = routing_response_;
common::util::FillHeader(node_->Name(), &routing_request_);
request_writer_->Write(routing_request_);
AINFO << "[TaskManagerComponent]Reach begin/end point: "
<< "routing manager send a routing request. ";
rate.Sleep();
if (!routing_response_.has_header()) {
AINFO << "[TaskManagerComponent]routing failed";
return false;
}
if (last_routing_response_.has_header()) {
if (last_routing_response_.header().sequence_num() ==
routing_response_.header().sequence_num()) {
AINFO << "[TaskManagerComponent]No routing response: "
<< "new routing failed";
return false;
}
}
}
rate.Sleep();
}
} else if (task->task_type() == PARKING_ROUTING) {
parking_routing_manager_ = std::make_shared<ParkingRoutingManager>();
parking_routing_manager_->ConstructParkingRoutingRequest(
task->mutable_parking_routing_task());
RoutingRequest msg;
msg.CopyFrom(task->parking_routing_task().routing_request());
request_writer_->Write(msg);
}
return true;
}
} // namespace task_manager
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/proto/task_manager_config.proto
|
syntax = "proto2";
package apollo.task_manager;
message TopicConfig {
optional string routing_request_topic = 1;
optional string routing_response_topic = 2;
optional string localization_pose_topic = 3;
optional string planning_topic = 4;
}
message TaskManagerConfig {
optional TopicConfig topic_config = 1;
}
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/proto/BUILD
|
## Auto generated by `proto_build_generator.py`
load("@rules_proto//proto:defs.bzl", "proto_library")
load("@rules_cc//cc:defs.bzl", "cc_proto_library")
load("//tools:python_rules.bzl", "py_proto_library")
load("//tools/install:install.bzl", "install", "install_files")
package(default_visibility = ["//visibility:public"])
install_files(
name = "py_pb_task_manager",
dest = "task_manager/python/modules/task_manager/proto",
files = [
":task_manager_config_py_pb2",
]
)
cc_proto_library(
name = "task_manager_config_cc_proto",
deps = [
":task_manager_config_proto",
],
)
proto_library(
name = "task_manager_config_proto",
srcs = ["task_manager_config.proto"],
)
py_proto_library(
name = "task_manager_config_py_pb2",
deps = [
":task_manager_config_proto",
],
)
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/dag/task_manager.dag
|
# Define all coms in DAG streaming.
module_config {
module_library : "/apollo/bazel-bin/modules/task_manager/libtask_manager_component.so"
components {
class_name : "TaskManagerComponent"
config {
name : "task_manager"
config_file_path: "/apollo/modules/task_manager/conf/task_manager_config.pb.txt"
flag_file_path: "/apollo/modules/task_manager/conf/task_manager.conf"
readers: [
{
channel: "/apollo/task_manager"
qos_profile: {
depth : 15
}
pending_queue_size: 50
}
]
}
}
}
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/common/task_manager_gflags.cc
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/task_manager/common/task_manager_gflags.h"
DEFINE_string(task_manager_node_name, "task_manager", "the name for this node");
DEFINE_double(threshold_for_destination_check, 1.0,
"meters, which is 100 feet. This threshold is used to check if"
"the vehicle reaches the destination");
DEFINE_double(plot_size_buffer, 0.2, "the size buffer of parking plot");
DEFINE_double(road_width_buffer, 0.0, "the size buffer of road width");
DEFINE_double(search_junction_threshold, 1.0,
"the threshold is used to search junction a certain range");
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/common/task_manager_gflags.h
|
/******************************************************************************
* Copyright 2020 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include "gflags/gflags.h"
DECLARE_string(task_manager_node_name);
DECLARE_double(threshold_for_destination_check);
DECLARE_double(plot_size_buffer);
DECLARE_double(road_width_buffer);
DECLARE_double(search_junction_threshold);
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/common/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library")
load("//tools:cpplint.bzl", "cpplint")
package(default_visibility = ["//visibility:public"])
cc_library(
name = "task_manager_gflags",
srcs = ["task_manager_gflags.cc"],
hdrs = ["task_manager_gflags.h"],
deps = [
"@com_github_gflags_gflags//:gflags",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/conf/task_manager_config.pb.txt
|
topic_config {
routing_request_topic: "/apollo/routing_request"
routing_response_topic: "/apollo/routing_response"
localization_pose_topic: "/apollo/localization/pose"
planning_topic: "/apollo/planning"
}
| 0
|
apollo_public_repos/apollo/modules/task_manager
|
apollo_public_repos/apollo/modules/task_manager/conf/task_manager.conf
|
--flagfile=/apollo/modules/common/data/global_flagfile.txt
--threshold_for_destination_check=10.0
--plot_size_buffer=0.2
--road_width_buffer=0.0
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/cyberfile_gpu.xml
|
<package format="2">
<name>planning-gpu</name>
<version>local</version>
<description>
Compared with previous versions, Apollo 7.0 adds a new dead end scenario, adds the "three-point turn", increases vehicle driving in and out ability, and expands the operation boundary of the urban road network. The "three-point turn" function is based on the open space planner framework and includes the following parts: scene conversion of dead ends, construction of open space ROI, and "three-point turn" trajectory planning.
</description>
<maintainer email="apollo-support@baidu.com">Apollo</maintainer>
<license>Apache License 2.0</license>
<url type="website">https://www.apollo.auto/</url>
<url type="repository">https://github.com/ApolloAuto/apollo</url>
<url type="bugtracker">https://github.com/ApolloAuto/apollo/issues</url>
<type>module</type>
<src_path url="https://github.com/ApolloAuto/apollo">//modules/planning</src_path>
<depend repo_name="com_github_gflags_gflags" lib_names="gflags">3rd-gflags-dev</depend>
<depend repo_name="com_google_absl" lib_names="absl">3rd-absl-dev</depend>
<depend repo_name="osqp">3rd-osqp-dev</depend>
<depend repo_name="com_github_google_glog" lib_names="glog">3rd-glog-dev</depend>
<depend repo_name="proj">3rd-proj-dev</depend>
<depend repo_name="tinyxml2" so_names="tinyxml2">libtinyxml2-dev</depend>
<depend repo_name="boost">3rd-boost-dev</depend>
<depend repo_name="opencv" lib_names="core,highgui,imgproc,imgcodecs">3rd-opencv-dev</depend>
<depend repo_name="ipopt">3rd-ipopt-dev</depend>
<depend repo_name="eigen">3rd-eigen3-dev</depend>
<depend repo_name="adolc" so_names="adolc">libadolc-dev</depend>
<depend repo_name="ad_rss_lib" lib_names="ad_rss">3rd-ad-rss-lib-dev</depend>
<depend type="binary" repo_name="cyber">cyber-dev</depend>
<depend type="binary" repo_name="common" lib_names="common">common-dev</depend>
<depend type="binary" repo_name="map" lib_names="map">map-dev</depend>
<depend repo_name="common-msgs" lib_names="common-msgs">common-msgs-dev</depend>
<depend>bazel-extend-tools-dev</depend>
<depend>3rd-mkl-dev</depend>
<depend repo_name="libtorch_cpu" lib_names="libtorch_cpu" condition="not gpu">3rd-libtorch-cpu-dev</depend>
<depend repo_name="libtorch_gpu" lib_names="libtorch_gpu" condition="gpu">3rd-libtorch-gpu-dev</depend>
<depend lib_names="protobuf" repo_name="com_google_protobuf">3rd-protobuf-dev</depend>
<depend expose="False">3rd-rules-python-dev</depend>
<depend expose="False">3rd-grpc-dev</depend>
<depend expose="False">3rd-bazel-skylib-dev</depend>
<depend expose="False">3rd-rules-proto-dev</depend>
<depend expose="False">3rd-py-dev</depend>
<depend expose="False">3rd-gpus-dev</depend>
<depend repo_name="com_google_googletest" lib_names="gtest,gtest_main">3rd-gtest-dev</depend>
</package>
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/cyberfile_cpu.xml
|
<package format="2">
<name>planning</name>
<version>local</version>
<description>
Compared with previous versions, Apollo 7.0 adds a new dead end scenario, adds the "three-point turn", increases vehicle driving in and out ability, and expands the operation boundary of the urban road network. The "three-point turn" function is based on the open space planner framework and includes the following parts: scene conversion of dead ends, construction of open space ROI, and "three-point turn" trajectory planning.
</description>
<maintainer email="apollo-support@baidu.com">Apollo</maintainer>
<license>Apache License 2.0</license>
<url type="website">https://www.apollo.auto/</url>
<url type="repository">https://github.com/ApolloAuto/apollo</url>
<url type="bugtracker">https://github.com/ApolloAuto/apollo/issues</url>
<type>module</type>
<src_path url="https://github.com/ApolloAuto/apollo">//modules/planning</src_path>
<depend repo_name="com_github_gflags_gflags" lib_names="gflags">3rd-gflags-dev</depend>
<depend repo_name="com_google_absl" lib_names="absl">3rd-absl-dev</depend>
<depend repo_name="osqp">3rd-osqp-dev</depend>
<depend repo_name="com_github_google_glog" lib_names="glog">3rd-glog-dev</depend>
<depend repo_name="proj">3rd-proj-dev</depend>
<depend repo_name="tinyxml2" so_names="tinyxml2">libtinyxml2-dev</depend>
<depend repo_name="boost">3rd-boost-dev</depend>
<depend repo_name="opencv" lib_names="core,highgui,imgproc,imgcodecs">3rd-opencv-dev</depend>
<depend repo_name="ipopt">3rd-ipopt-dev</depend>
<depend repo_name="eigen">3rd-eigen3-dev</depend>
<depend repo_name="adolc" so_names="adolc">libadolc-dev</depend>
<depend repo_name="ad_rss_lib" lib_names="ad_rss">3rd-ad-rss-lib-dev</depend>
<depend type="binary" repo_name="cyber">cyber-dev</depend>
<depend type="binary" repo_name="common" lib_names="common">common-dev</depend>
<depend type="binary" repo_name="map" lib_names="map">map-dev</depend>
<depend repo_name="common-msgs" lib_names="common-msgs">common-msgs-dev</depend>
<depend>bazel-extend-tools-dev</depend>
<depend>3rd-mkl-dev</depend>
<depend repo_name="libtorch_cpu" lib_names="libtorch_cpu" condition="not gpu">3rd-libtorch-cpu-dev</depend>
<depend repo_name="libtorch_gpu" lib_names="libtorch_gpu" condition="gpu">3rd-libtorch-gpu-dev</depend>
<depend lib_names="protobuf" repo_name="com_google_protobuf">3rd-protobuf-dev</depend>
<depend expose="False">3rd-rules-python-dev</depend>
<depend expose="False">3rd-grpc-dev</depend>
<depend expose="False">3rd-bazel-skylib-dev</depend>
<depend expose="False">3rd-rules-proto-dev</depend>
<depend expose="False">3rd-py-dev</depend>
<depend expose="False">3rd-gpus-dev</depend>
<depend repo_name="com_google_googletest" lib_names="gtest,gtest_main">3rd-gtest-dev</depend>
</package>
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/planning_base.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include <string>
#include <vector>
#include "modules/common_msgs/basic_msgs/pnc_point.pb.h"
#include "modules/common_msgs/chassis_msgs/chassis.pb.h"
#include "modules/common_msgs/dreamview_msgs/chart.pb.h"
#include "modules/common_msgs/localization_msgs/localization.pb.h"
#include "modules/common_msgs/perception_msgs/traffic_light_detection.pb.h"
#include "modules/common_msgs/planning_msgs/planning.pb.h"
#include "modules/common_msgs/prediction_msgs/prediction_obstacle.pb.h"
#include "modules/common_msgs/routing_msgs/routing.pb.h"
#include "modules/common/status/status.h"
#include "modules/common/vehicle_state/vehicle_state_provider.h"
#include "modules/map/hdmap/hdmap.h"
#include "modules/planning/common/dependency_injector.h"
#include "modules/planning/common/frame.h"
#include "modules/planning/common/local_view.h"
#include "modules/planning/common/trajectory/publishable_trajectory.h"
#include "modules/planning/planner/planner_dispatcher.h"
#include "modules/planning/planner/planner.h"
#include "modules/planning/proto/planning_config.pb.h"
#include "modules/planning/proto/traffic_rule_config.pb.h"
/**
* @namespace apollo::planning
* @brief apollo::planning
*/
namespace apollo {
namespace planning {
/**
* @class planning
*
* @brief PlanningBase module main class.
*/
class PlanningBase {
public:
PlanningBase() = delete;
explicit PlanningBase(const std::shared_ptr<DependencyInjector>& injector);
virtual ~PlanningBase();
virtual apollo::common::Status Init(const PlanningConfig& config);
virtual std::string Name() const = 0;
virtual void RunOnce(const LocalView& local_view,
ADCTrajectory* const adc_trajectory) = 0;
/**
* @brief Plan the trajectory given current vehicle state
*/
virtual apollo::common::Status Plan(
const double current_time_stamp,
const std::vector<common::TrajectoryPoint>& stitching_trajectory,
ADCTrajectory* const trajectory) = 0;
protected:
virtual void FillPlanningPb(const double timestamp,
ADCTrajectory* const trajectory_pb);
LocalView local_view_;
const hdmap::HDMap* hdmap_ = nullptr;
double start_time_ = 0.0;
size_t seq_num_ = 0;
PlanningConfig config_;
TrafficRuleConfigs traffic_rule_configs_;
std::unique_ptr<Frame> frame_;
std::unique_ptr<Planner> planner_;
std::unique_ptr<PublishableTrajectory> last_publishable_trajectory_;
std::unique_ptr<PlannerDispatcher> planner_dispatcher_;
std::shared_ptr<DependencyInjector> injector_;
};
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/on_lane_planning.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include <string>
#include <vector>
#include "modules/planning/common/smoothers/smoother.h"
#include "modules/planning/planner/on_lane_planner_dispatcher.h"
#include "modules/planning/planning_base.h"
/**
* @namespace apollo::planning
* @brief apollo::planning
*/
namespace apollo {
namespace planning {
/**
* @class planning
*
* @brief Planning module main class. It processes GPS and IMU as input,
* to generate planning info.
*/
class OnLanePlanning : public PlanningBase {
public:
explicit OnLanePlanning(const std::shared_ptr<DependencyInjector>& injector)
: PlanningBase(injector) {
planner_dispatcher_ = std::make_unique<OnLanePlannerDispatcher>();
}
virtual ~OnLanePlanning();
/**
* @brief Planning name.
*/
std::string Name() const override;
/**
* @brief module initialization function
* @return initialization status
*/
common::Status Init(const PlanningConfig& config) override;
/**
* @brief main logic of the planning module, runs periodically triggered by
* timer.
*/
void RunOnce(const LocalView& local_view,
ADCTrajectory* const ptr_trajectory_pb) override;
common::Status Plan(
const double current_time_stamp,
const std::vector<common::TrajectoryPoint>& stitching_trajectory,
ADCTrajectory* const trajectory) override;
private:
common::Status InitFrame(const uint32_t sequence_num,
const common::TrajectoryPoint& planning_start_point,
const common::VehicleState& vehicle_state);
common::VehicleState AlignTimeStamp(const common::VehicleState& vehicle_state,
const double curr_timestamp) const;
void ExportReferenceLineDebug(planning_internal::Debug* debug);
bool CheckPlanningConfig(const PlanningConfig& config);
void GenerateStopTrajectory(ADCTrajectory* ptr_trajectory_pb);
void ExportFailedLaneChangeSTChart(const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart);
void ExportOnLaneChart(const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart);
void ExportOpenSpaceChart(const planning_internal::Debug& debug_info,
const ADCTrajectory& trajectory_pb,
planning_internal::Debug* debug_chart);
void AddOpenSpaceOptimizerResult(const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart);
void AddPartitionedTrajectory(const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart);
void AddStitchSpeedProfile(planning_internal::Debug* debug_chart);
void AddPublishedSpeed(const ADCTrajectory& trajectory_pb,
planning_internal::Debug* debug_chart);
void AddPublishedAcceleration(const ADCTrajectory& trajectory_pb,
planning_internal::Debug* debug);
void AddFallbackTrajectory(const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart);
private:
routing::RoutingResponse last_routing_;
std::unique_ptr<ReferenceLineProvider> reference_line_provider_;
Smoother planning_smoother_;
};
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/planning-gpu.BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library")
cc_library(
name = "planning",
includes = ["include"],
hdrs = glob(["include/**/*.h"]),
srcs = glob(["lib/**/*.so*"]),
include_prefix = "modules/planning",
strip_include_prefix = "include",
visibility = ["//visibility:public"],
)
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/README.md
|
# Planning
## Introduction
Prior to the 5.5 release, Apollo uses the same configuration and parameters to
plan different driving scenarios. Although linear and easy to implement, this
approach was not flexible or scenario specific. As Apollo matures and takes on
different road conditions and driving use cases, we felt the need to move to a
more modular, scenario specific and wholistic approach for planning its
trajectory. In this approach, each driving use case is treated as a different
driving scenario. This is useful because an issue now reported in a particular
scenario can be fixed without affecting the working of other scenarios as
opposed to the previous versions, wherein an issue fix affected other driving
use cases as they were all treated as a single driving scenario.
Apollo 5.5, which focuses on curb-to-curb autonomous driving on urban roads,
introduced 2 new planning scenarios.
Apollo 6.0 extended the technology to incorporate data-driven mothedologies to tackle trajectory planning problems with learning-based models, and introduced two new planning modes: E2E mode and Hybrid mode, by which the new capability of dynamically nudginng moving obstacles are demonstrated. In these two modes, a series of APIs is also defined where developers can generate their own training data and integrate their own models.
**Note:** The current development of E2E mode is in an early stage where the model is trained for the dynamic nudge scenario as a research demonstration purpose. The capability of the model is limited, and suboptimality is expected when it is tested with a wider selection of scenarios. E2E mode and Hybrid mode are not tested on real roads yet, but rather serve as a baseline to promote and encourage extensive research on learning based planning. All developers are welcome to collaborate with us by any means including algorithms, models and data.
## E2E Mode
### How to Enable
- Change the configuration "learning_mode" in apollo/modules/planning/conf/planning_config.pb.txt to be "E2E_TEST" if Apollo is run in simulation or "E2E" on real vehicle
- Change the configuration "model_type" in apollo/modules/planning/conf/scenario/learning_model_sample_config.pb.txt to be either "CNN_LSTM" or "CNN" and adapt the following "cpu_model_file" and "gpu_model_file" file paths. "CNN_LSTM" is the preferred model for now.
### Model Inputs and Outputs
- Model input consists of a birdview image centered by vehicle pose and vehicle current velocity.
- Model output is planning trajectory
## Hybrid Mode
### How to Enable
In configuration file,
```
./modules/planning/conf/planning_config.pb.txt
```
set learning_mode: `learning_mode: ` as `HYBRID` for road test or `HYBRID_TEST` for simulation.
### Parameters
The configurable parameters in hybrid model are listed in the configuration file
```
modules/planning/conf/scenario/lane_follow_hybrid_config.pb.txt
```
The parameter `path_reference_l_weight` is for adjusting hybrid model path output. A larger value of `path_reference_l_weight` means higher penalty of the difference between hybrid model path and learning model path in lateral direction.
## Apollo 5.5 vs E2E Mode vs Hybrid Mode
We demonstrate simulation results on a dynamic nudge scenario with Apollo 5.5, E2E mode, and Hybrid mode.
- Apollo 5.5
- E2E Mode
- Hybrid Mode
## Driving Scenarios
There are 5 main driving scenarios that we will focus on Lane Follow, Intersection, Pull-Over, and the newly introduced Park-and-go and Emergency. Let's dive into them individually:
### Lane Follow - Default
As seen in the figure below, the lane-follow scenario, our default driving scenario, includes but is not limited to driving in a single lane (like cruising) or changing lane, following basic traffic convention or basic turning.
> Note: Side Pass
>
> > While the functionality of side pass still exists, it has now been made universal rather than limiting it to a type of scenario. The side-pass feature is incorporated as part of the path-bounds decider task. You can choose to turn it on or off by properly configuring the path-lane-borrow decider task. For example, if you want the vehicle to be agile, then turn side-pass on for all scenarios; if you feel it not safe to side-pass in intersections, then turn it off for those related scenarios.
### Intersection
The new intersection scenario includes STOP Signs, Traffic Lights and Bare Intersections which do not have either a light or a sign.
#### STOP Sign
There are two separate driving scenarios for STOP signs:
- **Unprotected**: In this scenario, the car is expected to navigate through a crossroad having a two-way STOP. Our ADC therefore has to creep through and gauge the crossroad's traffic density before continuing onto its path.
- **Protected**: In this scenario, the car is expected to navigate through a crossroad having a four-way STOP. Our ADC will have to gauge the cars that come to a STOP before it and understand its position in the queue before moving.
In order to safely pass through a STOP sign, both protected and unprotected, the following steps are performed:
- Arriving at the STOP sign: Perceive all other cars or obstacles that are currently waiting at the other stop signs
- Come to a complete stop: Monitor to see if the cars that were previously stationary at other STOP signs have moved or not. It is essential that the cars that arrived before have all left
- Move forward slightly (Creep): Check to see if any other car is moving or in the case of unprotected stop, check to see if there are any oncoming vehicles on either side of the lane
- Safely move through the crossroad
> Note:
>
> > The team is working to add additional driving scenarios into our planner. One such example is handling Traffic Lights.
#### Traffic Light
In order to safely and smoothly pass through a traffic light, we created 3 driving scenarios:
- **Protected**: In this scenario, our ego car has to pass through an intersection with a clear traffic light indicator. A left arrow or right arrow in green for the corresponding turn.
- **Unprotected Left**: In this scenario, our ego car will have to make a left turn without a distinct light, meaning the car would need to yield to oncoming traffic. Just like in the unprotected STOP scenario, our ego car would have to creep to ensure that it is safe to cross the intersection before safely moving through the lane.
- **Unprotected Right**: In this scenario, our ego car is expected to make an unprotected right turn while yielding to oncoming traffic. Our ego car will need to creep slowly and gauge the traffic and then make a safe turn.
As discussed above, based on the three driving scenarios, the following 3 steps are performed:
- **Stop/Approach**: If a stop is required, our ego car will stop in front of traffic light stop line
- **Move forward slightly (Creep)**: Check to see if any other car is moving or in the case of unprotected turns, check to see if there are any oncoming vehicles on either side of the lane
- **Move**: Safely drive through the intersection
#### Bare Intersection
Bare intersection is a scenario designated to an intersection without either a STOP sign or a traffic light. In this scenario, the following steps are performed:
- **Approach**: Reach the intersection
- **Move forward slightly (Creep)**: Check to see if any other car is moving or in the case of unprotected stop, check to see if there are any oncoming vehicles on either side of the lane
- **Move**: Safely move through the intersection
### Park
The Apollo team is proud to introduce Open Space Planner, a new planning algorithm that can be used for several use cases especially the parking scenario. To learn more about Open Space Planner, please refer to [Open Space Planner Algorithm](https://github.com/ApolloAuto/apollo/blob/master/docs/specs/Open_Space_Planner.md)
#### Valet
The Valet scenario was designed to safely park your ego car in a targeted parking spot. There are 2 main stages that are performed in order to park your ego car:
1. **Approaching the Parking Spot**: In this stage, standard planning algorithms are used to approach the designated parking spot. The car will gradually cruise to a halt once it has found the right stopping point required in order to reverse into the parking spot as seen in the image below
2. **Parking**: In this stage, Open Space Planner algorithm is used to generate a zig-zag trajectory which involves both forward and reverse driving (gear changes) in order to safely park the ego car. A sample trajectory generated for the scenario in the previous image, can be seen below:
#### Pull Over
The Pull Over scenario was designed especially for maneuvering to the side of the road upon reaching your destination like for curb-side parallel parking. There are 3 main stages to accomplish the pull over scenario.
1. **Approaching**: In this stage, as there is no clear designated parking spot, the ego car simply approaches the side of the road where it seems feasible to park. Standard Planning algorithms are used for this stage. Once it comes to a halt, the second stage begins. An example of stage 1 can be seen in the image below:
2. **Retry Approach Parking**: In this stage the ego car adjusts itself to enter the parking spot. It is similar to the `Approach Parking Spot` case in the Valet scenario. An example of stage 2 can be seen in the image below:
3. **Retry Parking**: This stage uses Open Space Planner to parallel park the vehicle. A zig-zag trajectory is generated to help the ego car park itself on the side of the road. A sample trajectory generated for the scenario in the previous image, can be seen below:
There is a special case in the Pull Over scenario that does not need the Open Space Planner stage. This case occurs when there are no obstacles blocking the curb-side parking of the ego car. An example can be seen below. In such a case, the car simply approaches the parking spot and then enters the spot using standard planning.
### Park-and-go
Apollo 5.5 which focuses on curb-to-curb driving introduces the Park-and-go scenario which was designed to handle curb side parking, planning a new trajectory to the next destination and then driving along that trajectory. This scenario is extremely useful in situations like curb-side delivery or passenger pickup or drop-off. This scenario combines Open Space Planner along with other traditional trajectory planners to ensure that the car not only parks safely but is also able to exit per the new trajectory.
## Emergency
The Emergency scenario is another newly introduced scenario in Apollo 5.5, developed to ensure that the vehicle can be brought to a stop safely in the situation of a given trigger event (either via human input or due to a failure in one or more of the vehicle's hardware or software modules). This scenario is extremely crucial to urban driving as one often encounters several unforeseen situations on the road that requires the vehicle to come to a complete stop. There are two types of emergency stops that are performed using this scenario:
1. **Pull Over and Stop**: In this scenario, the autonomous car uses Open Space Planner to pull-over and then come to a full stop on the curb-side
2. **In Lane Stop**: In this scenario, the autonomous car comes to a complete stop in its lane. In this situation the car is well aware of its surrounding obstacles to prevent any rear-end collisions and ensure not just the safety of itself but also the vehicles around it.
## Planning Module Architecture
In Apollo 5.5, the Planning module architecture has been modified to incorporate new curb-to-curb driving scenarios on urban roads. As seen in the figure below, we have 2 new complex scenarios Emergency and Park-and-go. In order to plan these scenarios effectively, we have 2 new Deciders - Path Reuse Decider and Speed Bound Decider and have updated existing deciders making the planning architecture robust and flexible enough to handle many different types of urban road driving scenarios.
Each driving scenario has its set of driving parameters that are unique to that scenario making it safer, efficient, easier to customize and debug and more flexible.
> Note:
>
> > If you wish to include your own driving scenarios, please refer to existing scenarios as a reference. We currently do not have a template for writing your own planning scenario.
## Related Paper
1. [He R, Zhou J, Jiang S, Wang Y, Tao J, Song S, Hu J, Miao J, Luo Q. "TDR-OBCA: A Reliable Planner for Autonomous Driving in Free-Space Environment." *arXiv preprint arXiv:2009.11345.* ](https://arxiv.org/pdf/2009.11345.pdf)
2. [Zhou J, He R, Wang Y, Jiang S, Zhu Z, Hu J, Miao J, Luo Q. "DL-IAPS and PJSO: A Path/Speed Decoupled Trajectory Optimization and its Application in Autonomous Driving." *arXiv preprint arXiv:2009.11135.*](https://arxiv.org/pdf/2009.11135.pdf)
| 0
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apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/README_cn.md
|
# 规划
## 介绍
Apollo的之前版本，包含3.0都是用了相同的配置和参数规划不同的场景，这种方法虽然线性且实现简单，但不够灵活或用于特定场景。随着Apollo的成熟并承担不同的道路条件和驾驶用例，我们认为有必要采用更加模块化、适用于特定场景和整体的方法来规划其轨迹。
在这个方法中，每个驾驶用例都被当作不同的驾驶场景。这样做非常有用，因为与先前的版本相比，现在在特定场景中报告的问题可以在不影响其他场景的工作的情况下得到修复，其中问题修复影响其他驾驶用例，因为它们都被当作单个驾驶场景处理。
## 驾驶场景
Apollo3.5主要聚焦在三个主要驾驶场景，即：
### 车道保持 - 默认
如下图所示，车道保持场景（我们的默认驾驶场景）包括但不限于在单车道（如巡航）或换道行驶，遵循基本的交通约定或基本转弯。
### Side Pass
在这种情况下，如果在自动驾驶车辆（ADC）的车道上有静态车辆或静态障碍物，并且车辆不能在不接触障碍物的情况下安全地通过车道，则执行以下策略：
- 检查邻近车道是否接近通行
- 如果无车辆，进行绕行，绕过当前车道进入邻道
- 一旦障碍物安全通过，回到原车道上
### 停止标识
停止标识有两种分离的驾驶场景：
1、未保护：在这种情况下，汽车预计会通过具有双向停车位的十字路口。因此，我们的ADC必须爬过并测量十字路口的交通密度，然后才能继续走上它的道路。
2、受保护：在此场景中，汽车预期通过具有四向停车位的十字路口导航。我们的ADC将必须对在它之前停下来的汽车进行测量，并在移动之前了解它在队列中的位置。
为了安全地通过受保护和未受保护的停止标志，执行逻辑如下：
- 到达停车标志处：感知正等待在其他停车标志处的所有汽车或障碍物；
- 完全停止：Monitor检查之前停在其他停车标志处的汽车是否已经移动。以前到达的汽车必须全部离开；
- 稍微向前移动(爬行)：检查是否有其他车辆正在移动或在无保护停车的情况下，检查车道两侧是否有迎面而来的车辆
- 安全通过十字路口
```
Note:
Apollo团队正在努力增加额外的驾驶场景到规划器。其中一个例子是处理交通灯。
```
## Planning 模块架构
Apollo 3.5 Planning模块的架构已经改变，以反映我们针对不同驾驶场景的模块化方法。
如下图所示，在规划器中，是上面讨论的各个驾驶场景及其处理逻辑。
每个驾驶场景都有其独特的驾驶参数集，这些参数使该场景更安全、高效、更易于定制和调试，并且更加灵活。每个阶段可配置的，且被划分为 **任务**，并且可以通过编辑该场景的`config`文件来移动或创建每个任务。
部分重要特性包含如下：
- Apollo FSM（finite state machine）:一个有限状态机，与高清地图确定车辆状态给定其位置和路线。
- Planning Dispatcher: 根据车辆的状态和其他相关信息，调用合适的Planner
- Planner:获取所需的上下文数据和其他信息，确定相应的车辆意图，执行该意图所需的规划任务并生成规划轨迹。它还将更新未来作业的上下文。
- Deciders & Optimizers :一组实现决策任务和各种优化的无状态库。优化器特别优化车辆的轨迹和速度。决策者是基于规则的分类决策者，他们建议何时换车道、何时停车、何时爬行(慢速行进)或爬行何时完成。
- 黄色框：这些框被包含在未来的场景和/或开发人员中，以便基于现实世界的驱动用例贡献他们自己的场景
```
Note:
如果您希望包括您自己的驾驶场景，请参考现有方案作为参考。我们目前没有用于编写您自己的规划场景的模板。
```
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/on_lane_planning.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/planning/on_lane_planning.h"
#include <algorithm>
#include <limits>
#include <list>
#include <utility>
#include "gtest/gtest_prod.h"
#include "absl/strings/str_cat.h"
#include "modules/common_msgs/planning_msgs/planning_internal.pb.h"
#include "modules/common_msgs/routing_msgs/routing.pb.h"
#include "modules/planning/proto/planning_semantic_map_config.pb.h"
#include "cyber/common/file.h"
#include "cyber/common/log.h"
#include "cyber/time/clock.h"
#include "modules/common/math/quaternion.h"
#include "modules/common/vehicle_state/vehicle_state_provider.h"
#include "modules/map/hdmap/hdmap_util.h"
#include "modules/planning/common/ego_info.h"
#include "modules/planning/common/history.h"
#include "modules/planning/common/planning_context.h"
#include "modules/planning/common/planning_gflags.h"
#include "modules/planning/common/trajectory_stitcher.h"
#include "modules/planning/common/util/util.h"
#include "modules/planning/learning_based/img_feature_renderer/birdview_img_feature_renderer.h"
#include "modules/planning/planner/rtk/rtk_replay_planner.h"
#include "modules/planning/reference_line/reference_line_provider.h"
#include "modules/planning/tasks/task_factory.h"
#include "modules/planning/traffic_rules/traffic_decider.h"
namespace apollo {
namespace planning {
using apollo::canbus::Chassis;
using apollo::common::EngageAdvice;
using apollo::common::ErrorCode;
using apollo::common::Status;
using apollo::common::TrajectoryPoint;
using apollo::common::VehicleState;
using apollo::common::VehicleStateProvider;
using apollo::common::math::Vec2d;
using apollo::cyber::Clock;
using apollo::dreamview::Chart;
using apollo::hdmap::HDMapUtil;
using apollo::planning_internal::SLFrameDebug;
using apollo::planning_internal::SpeedPlan;
using apollo::planning_internal::STGraphDebug;
void SetChartminmax(apollo::dreamview::Chart* chart, std::string label_name_x,
std::string label_name_y) {
auto* options = chart->mutable_options();
double xmin(std::numeric_limits<double>::max()),
xmax(std::numeric_limits<double>::lowest()),
ymin(std::numeric_limits<double>::max()),
ymax(std::numeric_limits<double>::lowest());
for (int i = 0; i < chart->line_size(); i++) {
auto* line = chart->mutable_line(i);
for (auto& pt : line->point()) {
xmin = std::min(xmin, pt.x());
ymin = std::min(ymin, pt.y());
xmax = std::max(xmax, pt.x());
ymax = std::max(ymax, pt.y());
}
auto* properties = line->mutable_properties();
(*properties)["borderWidth"] = "2";
(*properties)["pointRadius"] = "0";
(*properties)["lineTension"] = "0";
(*properties)["fill"] = "false";
(*properties)["showLine"] = "true";
}
options->mutable_x()->set_min(xmin);
options->mutable_x()->set_max(xmax);
options->mutable_x()->set_label_string(label_name_x);
options->mutable_y()->set_min(ymin);
options->mutable_y()->set_max(ymax);
options->mutable_y()->set_label_string(label_name_y);
// Set chartJS's dataset properties
}
OnLanePlanning::~OnLanePlanning() {
if (reference_line_provider_) {
reference_line_provider_->Stop();
}
planner_->Stop();
injector_->frame_history()->Clear();
injector_->history()->Clear();
injector_->planning_context()->mutable_planning_status()->Clear();
last_routing_.Clear();
injector_->ego_info()->Clear();
}
std::string OnLanePlanning::Name() const { return "on_lane_planning"; }
Status OnLanePlanning::Init(const PlanningConfig& config) {
config_ = config;
if (!CheckPlanningConfig(config_)) {
return Status(ErrorCode::PLANNING_ERROR,
"planning config error: " + config_.DebugString());
}
PlanningBase::Init(config_);
planner_dispatcher_->Init();
ACHECK(apollo::cyber::common::GetProtoFromFile(
FLAGS_traffic_rule_config_filename, &traffic_rule_configs_))
<< "Failed to load traffic rule config file "
<< FLAGS_traffic_rule_config_filename;
// clear planning history
injector_->history()->Clear();
// clear planning status
injector_->planning_context()->mutable_planning_status()->Clear();
// load map
hdmap_ = HDMapUtil::BaseMapPtr();
ACHECK(hdmap_) << "Failed to load map";
// instantiate reference line provider
reference_line_provider_ = std::make_unique<ReferenceLineProvider>(
injector_->vehicle_state(), hdmap_);
reference_line_provider_->Start();
// dispatch planner
planner_ = planner_dispatcher_->DispatchPlanner(config_, injector_);
if (!planner_) {
return Status(
ErrorCode::PLANNING_ERROR,
"planning is not initialized with config : " + config_.DebugString());
}
if (config_.learning_mode() != PlanningConfig::NO_LEARNING) {
PlanningSemanticMapConfig renderer_config;
ACHECK(apollo::cyber::common::GetProtoFromFile(
FLAGS_planning_birdview_img_feature_renderer_config_file,
&renderer_config))
<< "Failed to load renderer config"
<< FLAGS_planning_birdview_img_feature_renderer_config_file;
BirdviewImgFeatureRenderer::Instance()->Init(renderer_config);
}
start_time_ = Clock::NowInSeconds();
return planner_->Init(config_);
}
Status OnLanePlanning::InitFrame(const uint32_t sequence_num,
const TrajectoryPoint& planning_start_point,
const VehicleState& vehicle_state) {
frame_.reset(new Frame(sequence_num, local_view_, planning_start_point,
vehicle_state, reference_line_provider_.get()));
if (frame_ == nullptr) {
return Status(ErrorCode::PLANNING_ERROR, "Fail to init frame: nullptr.");
}
// Get the parking space information from routing request of local view.
auto& routing_request = local_view_.routing->routing_request();
if (routing_request.has_parking_info() &&
routing_request.parking_info().has_parking_space_id()) {
*(frame_->mutable_open_space_info()->mutable_target_parking_spot_id()) =
routing_request.parking_info().parking_space_id();
} else {
ADEBUG << "No parking space id from routing";
}
std::list<ReferenceLine> reference_lines;
std::list<hdmap::RouteSegments> segments;
if (!reference_line_provider_->GetReferenceLines(&reference_lines,
&segments)) {
const std::string msg = "Failed to create reference line";
AERROR << msg;
return Status(ErrorCode::PLANNING_ERROR, msg);
}
DCHECK_EQ(reference_lines.size(), segments.size());
auto forward_limit =
hdmap::PncMap::LookForwardDistance(vehicle_state.linear_velocity());
for (auto& ref_line : reference_lines) {
if (!ref_line.Segment(Vec2d(vehicle_state.x(), vehicle_state.y()),
FLAGS_look_backward_distance, forward_limit)) {
const std::string msg = "Fail to shrink reference line.";
AERROR << msg;
return Status(ErrorCode::PLANNING_ERROR, msg);
}
}
for (auto& seg : segments) {
if (!seg.Shrink(Vec2d(vehicle_state.x(), vehicle_state.y()),
FLAGS_look_backward_distance, forward_limit)) {
const std::string msg = "Fail to shrink routing segments.";
AERROR << msg;
return Status(ErrorCode::PLANNING_ERROR, msg);
}
}
auto status = frame_->Init(
injector_->vehicle_state(), reference_lines, segments,
reference_line_provider_->FutureRouteWaypoints(), injector_->ego_info());
if (!status.ok()) {
AERROR << "failed to init frame:" << status.ToString();
return status;
}
return Status::OK();
}
// TODO(all): fix this! this will cause unexpected behavior from controller
void OnLanePlanning::GenerateStopTrajectory(ADCTrajectory* ptr_trajectory_pb) {
ptr_trajectory_pb->clear_trajectory_point();
const auto& vehicle_state = injector_->vehicle_state()->vehicle_state();
const double max_t = FLAGS_fallback_total_time;
const double unit_t = FLAGS_fallback_time_unit;
TrajectoryPoint tp;
auto* path_point = tp.mutable_path_point();
path_point->set_x(vehicle_state.x());
path_point->set_y(vehicle_state.y());
path_point->set_theta(vehicle_state.heading());
path_point->set_s(0.0);
tp.set_v(0.0);
tp.set_a(0.0);
for (double t = 0.0; t < max_t; t += unit_t) {
tp.set_relative_time(t);
auto next_point = ptr_trajectory_pb->add_trajectory_point();
next_point->CopyFrom(tp);
}
}
void OnLanePlanning::RunOnce(const LocalView& local_view,
ADCTrajectory* const ptr_trajectory_pb) {
// when rerouting, reference line might not be updated. In this case, planning
// module maintains not-ready until be restarted.
static bool failed_to_update_reference_line = false;
local_view_ = local_view;
const double start_timestamp = Clock::NowInSeconds();
const double start_system_timestamp =
std::chrono::duration<double>(
std::chrono::system_clock::now().time_since_epoch())
.count();
// localization
ADEBUG << "Get localization:"
<< local_view_.localization_estimate->DebugString();
// chassis
ADEBUG << "Get chassis:" << local_view_.chassis->DebugString();
Status status = injector_->vehicle_state()->Update(
*local_view_.localization_estimate, *local_view_.chassis);
VehicleState vehicle_state = injector_->vehicle_state()->vehicle_state();
const double vehicle_state_timestamp = vehicle_state.timestamp();
DCHECK_GE(start_timestamp, vehicle_state_timestamp)
<< "start_timestamp is behind vehicle_state_timestamp by "
<< start_timestamp - vehicle_state_timestamp << " secs";
if (!status.ok() || !util::IsVehicleStateValid(vehicle_state)) {
const std::string msg =
"Update VehicleStateProvider failed "
"or the vehicle state is out dated.";
AERROR << msg;
ptr_trajectory_pb->mutable_decision()
->mutable_main_decision()
->mutable_not_ready()
->set_reason(msg);
status.Save(ptr_trajectory_pb->mutable_header()->mutable_status());
// TODO(all): integrate reverse gear
ptr_trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, ptr_trajectory_pb);
GenerateStopTrajectory(ptr_trajectory_pb);
return;
}
if (start_timestamp - vehicle_state_timestamp <
FLAGS_message_latency_threshold) {
vehicle_state = AlignTimeStamp(vehicle_state, start_timestamp);
}
// Update reference line provider and reset pull over if necessary
reference_line_provider_->UpdateVehicleState(vehicle_state);
if (util::IsDifferentRouting(last_routing_, *local_view_.routing)) {
last_routing_ = *local_view_.routing;
ADEBUG << "last_routing_:" << last_routing_.ShortDebugString();
injector_->history()->Clear();
injector_->planning_context()->mutable_planning_status()->Clear();
reference_line_provider_->UpdateRoutingResponse(*local_view_.routing);
planner_->Init(config_);
}
failed_to_update_reference_line =
(!reference_line_provider_->UpdatedReferenceLine());
// early return when reference line fails to update after rerouting
if (failed_to_update_reference_line) {
const std::string msg = "Failed to update reference line after rerouting.";
AERROR << msg;
ptr_trajectory_pb->mutable_decision()
->mutable_main_decision()
->mutable_not_ready()
->set_reason(msg);
status.Save(ptr_trajectory_pb->mutable_header()->mutable_status());
ptr_trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, ptr_trajectory_pb);
GenerateStopTrajectory(ptr_trajectory_pb);
return;
}
// planning is triggered by prediction data, but we can still use an estimated
// cycle time for stitching
const double planning_cycle_time =
1.0 / static_cast<double>(FLAGS_planning_loop_rate);
std::string replan_reason;
std::vector<TrajectoryPoint> stitching_trajectory =
TrajectoryStitcher::ComputeStitchingTrajectory(
vehicle_state, start_timestamp, planning_cycle_time,
FLAGS_trajectory_stitching_preserved_length, true,
last_publishable_trajectory_.get(), &replan_reason);
injector_->ego_info()->Update(stitching_trajectory.back(), vehicle_state);
const uint32_t frame_num = static_cast<uint32_t>(seq_num_++);
status = InitFrame(frame_num, stitching_trajectory.back(), vehicle_state);
if (status.ok()) {
injector_->ego_info()->CalculateFrontObstacleClearDistance(
frame_->obstacles());
}
if (FLAGS_enable_record_debug) {
frame_->RecordInputDebug(ptr_trajectory_pb->mutable_debug());
}
ptr_trajectory_pb->mutable_latency_stats()->set_init_frame_time_ms(
Clock::NowInSeconds() - start_timestamp);
if (!status.ok()) {
AERROR << status.ToString();
if (FLAGS_publish_estop) {
// "estop" signal check in function "Control::ProduceControlCommand()"
// estop_ = estop_ || local_view_.trajectory.estop().is_estop();
// we should add more information to ensure the estop being triggered.
ADCTrajectory estop_trajectory;
EStop* estop = estop_trajectory.mutable_estop();
estop->set_is_estop(true);
estop->set_reason(status.error_message());
status.Save(estop_trajectory.mutable_header()->mutable_status());
ptr_trajectory_pb->CopyFrom(estop_trajectory);
} else {
ptr_trajectory_pb->mutable_decision()
->mutable_main_decision()
->mutable_not_ready()
->set_reason(status.ToString());
status.Save(ptr_trajectory_pb->mutable_header()->mutable_status());
GenerateStopTrajectory(ptr_trajectory_pb);
}
// TODO(all): integrate reverse gear
ptr_trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, ptr_trajectory_pb);
frame_->set_current_frame_planned_trajectory(*ptr_trajectory_pb);
const uint32_t n = frame_->SequenceNum();
injector_->frame_history()->Add(n, std::move(frame_));
return;
}
for (auto& ref_line_info : *frame_->mutable_reference_line_info()) {
TrafficDecider traffic_decider;
traffic_decider.Init(traffic_rule_configs_);
auto traffic_status =
traffic_decider.Execute(frame_.get(), &ref_line_info, injector_);
if (!traffic_status.ok() || !ref_line_info.IsDrivable()) {
ref_line_info.SetDrivable(false);
AWARN << "Reference line " << ref_line_info.Lanes().Id()
<< " traffic decider failed";
}
}
status = Plan(start_timestamp, stitching_trajectory, ptr_trajectory_pb);
for (const auto& p : ptr_trajectory_pb->trajectory_point()) {
ADEBUG << p.DebugString();
}
const auto end_system_timestamp =
std::chrono::duration<double>(
std::chrono::system_clock::now().time_since_epoch())
.count();
const auto time_diff_ms =
(end_system_timestamp - start_system_timestamp) * 1000;
ADEBUG << "total planning time spend: " << time_diff_ms << " ms.";
ptr_trajectory_pb->mutable_latency_stats()->set_total_time_ms(time_diff_ms);
ADEBUG << "Planning latency: "
<< ptr_trajectory_pb->latency_stats().DebugString();
if (!status.ok()) {
status.Save(ptr_trajectory_pb->mutable_header()->mutable_status());
AERROR << "Planning failed:" << status.ToString();
if (FLAGS_publish_estop) {
AERROR << "Planning failed and set estop";
// "estop" signal check in function "Control::ProduceControlCommand()"
// estop_ = estop_ || local_view_.trajectory.estop().is_estop();
// we should add more information to ensure the estop being triggered.
EStop* estop = ptr_trajectory_pb->mutable_estop();
estop->set_is_estop(true);
estop->set_reason(status.error_message());
}
}
ptr_trajectory_pb->set_is_replan(stitching_trajectory.size() == 1);
if (ptr_trajectory_pb->is_replan()) {
ptr_trajectory_pb->set_replan_reason(replan_reason);
}
if (frame_->open_space_info().is_on_open_space_trajectory()) {
FillPlanningPb(start_timestamp, ptr_trajectory_pb);
ADEBUG << "Planning pb:" << ptr_trajectory_pb->header().DebugString();
frame_->set_current_frame_planned_trajectory(*ptr_trajectory_pb);
} else {
auto* ref_line_task =
ptr_trajectory_pb->mutable_latency_stats()->add_task_stats();
ref_line_task->set_time_ms(reference_line_provider_->LastTimeDelay() *
1000.0);
ref_line_task->set_name("ReferenceLineProvider");
// TODO(all): integrate reverse gear
ptr_trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, ptr_trajectory_pb);
ADEBUG << "Planning pb:" << ptr_trajectory_pb->header().DebugString();
frame_->set_current_frame_planned_trajectory(*ptr_trajectory_pb);
if (FLAGS_enable_planning_smoother) {
planning_smoother_.Smooth(injector_->frame_history(), frame_.get(),
ptr_trajectory_pb);
}
}
const uint32_t n = frame_->SequenceNum();
injector_->frame_history()->Add(n, std::move(frame_));
}
void OnLanePlanning::ExportReferenceLineDebug(planning_internal::Debug* debug) {
if (!FLAGS_enable_record_debug) {
return;
}
for (auto& reference_line_info : *frame_->mutable_reference_line_info()) {
auto rl_debug = debug->mutable_planning_data()->add_reference_line();
rl_debug->set_id(reference_line_info.Lanes().Id());
rl_debug->set_length(reference_line_info.reference_line().Length());
rl_debug->set_cost(reference_line_info.Cost());
rl_debug->set_is_change_lane_path(reference_line_info.IsChangeLanePath());
rl_debug->set_is_drivable(reference_line_info.IsDrivable());
rl_debug->set_is_protected(reference_line_info.GetRightOfWayStatus() ==
ADCTrajectory::PROTECTED);
// store kappa and dkappa for performance evaluation
const auto& reference_points =
reference_line_info.reference_line().reference_points();
double kappa_rms = 0.0;
double dkappa_rms = 0.0;
double kappa_max_abs = std::numeric_limits<double>::lowest();
double dkappa_max_abs = std::numeric_limits<double>::lowest();
for (const auto& reference_point : reference_points) {
double kappa_sq = reference_point.kappa() * reference_point.kappa();
double dkappa_sq = reference_point.dkappa() * reference_point.dkappa();
kappa_rms += kappa_sq;
dkappa_rms += dkappa_sq;
kappa_max_abs = kappa_max_abs < kappa_sq ? kappa_sq : kappa_max_abs;
dkappa_max_abs = dkappa_max_abs < dkappa_sq ? dkappa_sq : dkappa_max_abs;
}
double reference_points_size = static_cast<double>(reference_points.size());
kappa_rms /= reference_points_size;
dkappa_rms /= reference_points_size;
kappa_rms = std::sqrt(kappa_rms);
dkappa_rms = std::sqrt(dkappa_rms);
rl_debug->set_kappa_rms(kappa_rms);
rl_debug->set_dkappa_rms(dkappa_rms);
rl_debug->set_kappa_max_abs(kappa_max_abs);
rl_debug->set_dkappa_max_abs(dkappa_max_abs);
bool is_off_road = false;
double minimum_boundary = std::numeric_limits<double>::infinity();
const double adc_half_width =
common::VehicleConfigHelper::GetConfig().vehicle_param().width() / 2.0;
const auto& reference_line_path =
reference_line_info.reference_line().GetMapPath();
const auto sample_s = 0.1;
const auto reference_line_length =
reference_line_info.reference_line().Length();
double average_offset = 0.0;
double sample_count = 0.0;
for (double s = 0.0; s < reference_line_length; s += sample_s) {
double left_width = reference_line_path.GetLaneLeftWidth(s);
double right_width = reference_line_path.GetLaneRightWidth(s);
average_offset += 0.5 * std::abs(left_width - right_width);
if (left_width < adc_half_width || right_width < adc_half_width) {
is_off_road = true;
}
if (left_width < minimum_boundary) {
minimum_boundary = left_width;
}
if (right_width < minimum_boundary) {
minimum_boundary = right_width;
}
++sample_count;
}
rl_debug->set_is_offroad(is_off_road);
rl_debug->set_minimum_boundary(minimum_boundary);
rl_debug->set_average_offset(average_offset / sample_count);
}
}
Status OnLanePlanning::Plan(
const double current_time_stamp,
const std::vector<TrajectoryPoint>& stitching_trajectory,
ADCTrajectory* const ptr_trajectory_pb) {
auto* ptr_debug = ptr_trajectory_pb->mutable_debug();
if (FLAGS_enable_record_debug) {
ptr_debug->mutable_planning_data()->mutable_init_point()->CopyFrom(
stitching_trajectory.back());
frame_->mutable_open_space_info()->set_debug(ptr_debug);
frame_->mutable_open_space_info()->sync_debug_instance();
}
auto status = planner_->Plan(stitching_trajectory.back(), frame_.get(),
ptr_trajectory_pb);
ptr_debug->mutable_planning_data()->set_front_clear_distance(
injector_->ego_info()->front_clear_distance());
if (frame_->open_space_info().is_on_open_space_trajectory()) {
frame_->mutable_open_space_info()->sync_debug_instance();
const auto& publishable_trajectory =
frame_->open_space_info().publishable_trajectory_data().first;
const auto& publishable_trajectory_gear =
frame_->open_space_info().publishable_trajectory_data().second;
publishable_trajectory.PopulateTrajectoryProtobuf(ptr_trajectory_pb);
ptr_trajectory_pb->set_gear(publishable_trajectory_gear);
// TODO(QiL): refine engage advice in open space trajectory optimizer.
auto* engage_advice = ptr_trajectory_pb->mutable_engage_advice();
// enable start auto from open_space planner.
if (injector_->vehicle_state()->vehicle_state().driving_mode() !=
Chassis::DrivingMode::Chassis_DrivingMode_COMPLETE_AUTO_DRIVE) {
engage_advice->set_advice(EngageAdvice::READY_TO_ENGAGE);
engage_advice->set_reason(
"Ready to engage when staring with OPEN_SPACE_PLANNER");
} else {
engage_advice->set_advice(EngageAdvice::KEEP_ENGAGED);
engage_advice->set_reason("Keep engage while in parking");
}
// TODO(QiL): refine the export decision in open space info
ptr_trajectory_pb->mutable_decision()
->mutable_main_decision()
->mutable_parking()
->set_status(MainParking::IN_PARKING);
if (FLAGS_enable_record_debug) {
// ptr_debug->MergeFrom(frame_->open_space_info().debug_instance());
frame_->mutable_open_space_info()->RecordDebug(ptr_debug);
ADEBUG << "Open space debug information added!";
// call open space info load debug
// TODO(Runxin): create a new flag to enable openspace chart
ExportOpenSpaceChart(ptr_trajectory_pb->debug(), *ptr_trajectory_pb,
ptr_debug);
}
} else {
const auto* best_ref_info = frame_->FindDriveReferenceLineInfo();
const auto* target_ref_info = frame_->FindTargetReferenceLineInfo();
if (!best_ref_info) {
const std::string msg = "planner failed to make a driving plan";
AERROR << msg;
if (last_publishable_trajectory_) {
last_publishable_trajectory_->Clear();
}
return Status(ErrorCode::PLANNING_ERROR, msg);
}
// Store current frame stitched path for possible speed fallback in next
// frames
DiscretizedPath current_frame_planned_path;
for (const auto& trajectory_point : stitching_trajectory) {
current_frame_planned_path.push_back(trajectory_point.path_point());
}
const auto& best_ref_path = best_ref_info->path_data().discretized_path();
std::copy(best_ref_path.begin() + 1, best_ref_path.end(),
std::back_inserter(current_frame_planned_path));
frame_->set_current_frame_planned_path(current_frame_planned_path);
ptr_debug->MergeFrom(best_ref_info->debug());
if (FLAGS_export_chart) {
ExportOnLaneChart(best_ref_info->debug(), ptr_debug);
} else {
ExportReferenceLineDebug(ptr_debug);
// Export additional ST-chart for failed lane-change speed planning
const auto* failed_ref_info = frame_->FindFailedReferenceLineInfo();
if (failed_ref_info) {
ExportFailedLaneChangeSTChart(failed_ref_info->debug(), ptr_debug);
}
}
ptr_trajectory_pb->mutable_latency_stats()->MergeFrom(
best_ref_info->latency_stats());
// set right of way status
ptr_trajectory_pb->set_right_of_way_status(
best_ref_info->GetRightOfWayStatus());
for (const auto& id : best_ref_info->TargetLaneId()) {
ptr_trajectory_pb->add_lane_id()->CopyFrom(id);
}
for (const auto& id : target_ref_info->TargetLaneId()) {
ptr_trajectory_pb->add_target_lane_id()->CopyFrom(id);
}
ptr_trajectory_pb->set_trajectory_type(best_ref_info->trajectory_type());
if (FLAGS_enable_rss_info) {
*ptr_trajectory_pb->mutable_rss_info() = best_ref_info->rss_info();
}
best_ref_info->ExportDecision(ptr_trajectory_pb->mutable_decision(),
injector_->planning_context());
// Add debug information.
if (FLAGS_enable_record_debug) {
auto* reference_line = ptr_debug->mutable_planning_data()->add_path();
reference_line->set_name("planning_reference_line");
const auto& reference_points =
best_ref_info->reference_line().reference_points();
double s = 0.0;
double prev_x = 0.0;
double prev_y = 0.0;
bool empty_path = true;
for (const auto& reference_point : reference_points) {
auto* path_point = reference_line->add_path_point();
path_point->set_x(reference_point.x());
path_point->set_y(reference_point.y());
path_point->set_theta(reference_point.heading());
path_point->set_kappa(reference_point.kappa());
path_point->set_dkappa(reference_point.dkappa());
if (empty_path) {
path_point->set_s(0.0);
empty_path = false;
} else {
double dx = reference_point.x() - prev_x;
double dy = reference_point.y() - prev_y;
s += std::hypot(dx, dy);
path_point->set_s(s);
}
prev_x = reference_point.x();
prev_y = reference_point.y();
}
}
last_publishable_trajectory_.reset(new PublishableTrajectory(
current_time_stamp, best_ref_info->trajectory()));
ADEBUG << "current_time_stamp: " << current_time_stamp;
last_publishable_trajectory_->PrependTrajectoryPoints(
std::vector<TrajectoryPoint>(stitching_trajectory.begin(),
stitching_trajectory.end() - 1));
last_publishable_trajectory_->PopulateTrajectoryProtobuf(ptr_trajectory_pb);
best_ref_info->ExportEngageAdvice(
ptr_trajectory_pb->mutable_engage_advice(),
injector_->planning_context());
}
return status;
}
bool OnLanePlanning::CheckPlanningConfig(const PlanningConfig& config) {
if (!config.has_standard_planning_config()) {
return false;
}
if (!config.standard_planning_config().has_planner_public_road_config()) {
return false;
}
// TODO(All): check other config params
return true;
}
void PopulateChartOptions(double x_min, double x_max, std::string x_label,
double y_min, double y_max, std::string y_label,
bool display, Chart* chart) {
auto* options = chart->mutable_options();
options->mutable_x()->set_min(x_min);
options->mutable_x()->set_max(x_max);
options->mutable_y()->set_min(y_min);
options->mutable_y()->set_max(y_max);
options->mutable_x()->set_label_string(x_label);
options->mutable_y()->set_label_string(y_label);
options->set_legend_display(display);
}
void AddSTGraph(const STGraphDebug& st_graph, Chart* chart) {
if (st_graph.name() == "DP_ST_SPEED_OPTIMIZER") {
chart->set_title("Speed Heuristic");
} else {
chart->set_title("Planning S-T Graph");
}
PopulateChartOptions(-2.0, 10.0, "t (second)", -10.0, 220.0, "s (meter)",
false, chart);
for (const auto& boundary : st_graph.boundary()) {
// from 'ST_BOUNDARY_TYPE_' to the end
std::string type =
StGraphBoundaryDebug_StBoundaryType_Name(boundary.type()).substr(17);
auto* boundary_chart = chart->add_polygon();
auto* properties = boundary_chart->mutable_properties();
(*properties)["borderWidth"] = "2";
(*properties)["pointRadius"] = "0";
(*properties)["lineTension"] = "0";
(*properties)["cubicInterpolationMode"] = "monotone";
(*properties)["showLine"] = "true";
(*properties)["showText"] = "true";
(*properties)["fill"] = "false";
if (type == "DRIVABLE_REGION") {
(*properties)["color"] = "\"rgba(0, 255, 0, 0.5)\"";
} else {
(*properties)["color"] = "\"rgba(255, 0, 0, 0.8)\"";
}
boundary_chart->set_label(boundary.name() + "_" + type);
for (const auto& point : boundary.point()) {
auto* point_debug = boundary_chart->add_point();
point_debug->set_x(point.t());
point_debug->set_y(point.s());
}
}
auto* speed_profile = chart->add_line();
auto* properties = speed_profile->mutable_properties();
(*properties)["color"] = "\"rgba(255, 255, 255, 0.5)\"";
for (const auto& point : st_graph.speed_profile()) {
auto* point_debug = speed_profile->add_point();
point_debug->set_x(point.t());
point_debug->set_y(point.s());
}
}
void AddSLFrame(const SLFrameDebug& sl_frame, Chart* chart) {
chart->set_title(sl_frame.name());
PopulateChartOptions(0.0, 80.0, "s (meter)", -8.0, 8.0, "l (meter)", false,
chart);
auto* sl_line = chart->add_line();
sl_line->set_label("SL Path");
for (const auto& sl_point : sl_frame.sl_path()) {
auto* point_debug = sl_line->add_point();
point_debug->set_x(sl_point.s());
point_debug->set_x(sl_point.l());
}
}
void AddSpeedPlan(
const ::google::protobuf::RepeatedPtrField<SpeedPlan>& speed_plans,
Chart* chart) {
chart->set_title("Speed Plan");
PopulateChartOptions(0.0, 80.0, "s (meter)", 0.0, 50.0, "v (m/s)", false,
chart);
for (const auto& speed_plan : speed_plans) {
auto* line = chart->add_line();
line->set_label(speed_plan.name());
for (const auto& point : speed_plan.speed_point()) {
auto* point_debug = line->add_point();
point_debug->set_x(point.s());
point_debug->set_y(point.v());
}
// Set chartJS's dataset properties
auto* properties = line->mutable_properties();
(*properties)["borderWidth"] = "2";
(*properties)["pointRadius"] = "0";
(*properties)["fill"] = "false";
(*properties)["showLine"] = "true";
if (speed_plan.name() == "DpStSpeedOptimizer") {
(*properties)["color"] = "\"rgba(27, 249, 105, 0.5)\"";
} else if (speed_plan.name() == "QpSplineStSpeedOptimizer") {
(*properties)["color"] = "\"rgba(54, 162, 235, 1)\"";
}
}
}
void OnLanePlanning::ExportFailedLaneChangeSTChart(
const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart) {
const auto& src_data = debug_info.planning_data();
auto* dst_data = debug_chart->mutable_planning_data();
for (const auto& st_graph : src_data.st_graph()) {
AddSTGraph(st_graph, dst_data->add_chart());
}
}
void OnLanePlanning::ExportOnLaneChart(
const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart) {
const auto& src_data = debug_info.planning_data();
auto* dst_data = debug_chart->mutable_planning_data();
for (const auto& st_graph : src_data.st_graph()) {
AddSTGraph(st_graph, dst_data->add_chart());
}
for (const auto& sl_frame : src_data.sl_frame()) {
AddSLFrame(sl_frame, dst_data->add_chart());
}
AddSpeedPlan(src_data.speed_plan(), dst_data->add_chart());
}
void OnLanePlanning::ExportOpenSpaceChart(
const planning_internal::Debug& debug_info,
const ADCTrajectory& trajectory_pb, planning_internal::Debug* debug_chart) {
// Export Trajectory Visualization Chart.
if (FLAGS_enable_record_debug) {
AddOpenSpaceOptimizerResult(debug_info, debug_chart);
AddPartitionedTrajectory(debug_info, debug_chart);
AddStitchSpeedProfile(debug_chart);
AddPublishedSpeed(trajectory_pb, debug_chart);
AddPublishedAcceleration(trajectory_pb, debug_chart);
// AddFallbackTrajectory(debug_info, debug_chart);
}
}
void OnLanePlanning::AddOpenSpaceOptimizerResult(
const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart) {
// if open space info provider success run
if (!frame_->open_space_info().open_space_provider_success()) {
return;
}
auto chart = debug_chart->mutable_planning_data()->add_chart();
auto open_space_debug = debug_info.planning_data().open_space();
chart->set_title("Open Space Trajectory Optimizer Visualization");
PopulateChartOptions(open_space_debug.xy_boundary(0) - 1.0,
open_space_debug.xy_boundary(1) + 1.0, "x (meter)",
open_space_debug.xy_boundary(2) - 1.0,
open_space_debug.xy_boundary(3) + 1.0, "y (meter)", true,
chart);
chart->mutable_options()->set_sync_xy_window_size(true);
chart->mutable_options()->set_aspect_ratio(0.9);
int obstacle_index = 1;
for (const auto& obstacle : open_space_debug.obstacles()) {
auto* obstacle_outline = chart->add_line();
obstacle_outline->set_label(absl::StrCat("Bdr", obstacle_index));
obstacle_index += 1;
for (int vertice_index = 0;
vertice_index < obstacle.vertices_x_coords_size(); vertice_index++) {
auto* point_debug = obstacle_outline->add_point();
point_debug->set_x(obstacle.vertices_x_coords(vertice_index));
point_debug->set_y(obstacle.vertices_y_coords(vertice_index));
}
// Set chartJS's dataset properties
auto* obstacle_properties = obstacle_outline->mutable_properties();
(*obstacle_properties)["borderWidth"] = "2";
(*obstacle_properties)["pointRadius"] = "0";
(*obstacle_properties)["lineTension"] = "0";
(*obstacle_properties)["fill"] = "false";
(*obstacle_properties)["showLine"] = "true";
}
auto smoothed_trajectory = open_space_debug.smoothed_trajectory();
auto* smoothed_line = chart->add_line();
smoothed_line->set_label("Smooth");
// size_t adc_label = 0;
for (int i = 0; i < smoothed_trajectory.vehicle_motion_point_size() / 2;
i++) {
auto& point = smoothed_trajectory.vehicle_motion_point(i);
const auto x = point.trajectory_point().path_point().x();
const auto y = point.trajectory_point().path_point().y();
// const auto heading = point.trajectory_point().path_point().theta();
/*
// Draw vehicle shape along the trajectory
auto* adc_shape = chart->add_car();
adc_shape->set_x(x);
adc_shape->set_y(y);
adc_shape->set_heading(heading);
adc_shape->set_color("rgba(54, 162, 235, 1)");
adc_shape->set_label(std::to_string(adc_label));
adc_shape->set_hide_label_in_legend(true);
++adc_label;
*/
// Draw vehicle trajectory points
auto* point_debug = smoothed_line->add_point();
point_debug->set_x(x);
point_debug->set_y(y);
}
// Set chartJS's dataset properties
auto* smoothed_properties = smoothed_line->mutable_properties();
(*smoothed_properties)["borderWidth"] = "2";
(*smoothed_properties)["pointRadius"] = "0";
(*smoothed_properties)["lineTension"] = "0";
(*smoothed_properties)["fill"] = "false";
(*smoothed_properties)["showLine"] = "true";
auto warm_start_trajectory = open_space_debug.warm_start_trajectory();
auto* warm_start_line = chart->add_line();
warm_start_line->set_label("WarmStart");
for (int i = 0; i < warm_start_trajectory.vehicle_motion_point_size() / 2;
i++) {
auto* point_debug = warm_start_line->add_point();
auto& point = warm_start_trajectory.vehicle_motion_point(i);
point_debug->set_x(point.trajectory_point().path_point().x());
point_debug->set_y(point.trajectory_point().path_point().y());
}
// Set chartJS's dataset properties
auto* warm_start_properties = warm_start_line->mutable_properties();
(*warm_start_properties)["borderWidth"] = "2";
(*warm_start_properties)["pointRadius"] = "0";
(*warm_start_properties)["lineTension"] = "0";
(*warm_start_properties)["fill"] = "false";
(*warm_start_properties)["showLine"] = "true";
}
void OnLanePlanning::AddPartitionedTrajectory(
const planning_internal::Debug& debug_info,
planning_internal::Debug* debug_chart) {
// if open space info provider success run
if (!frame_->open_space_info().open_space_provider_success()) {
return;
}
const auto& open_space_debug = debug_info.planning_data().open_space();
const auto& chosen_trajectories =
open_space_debug.chosen_trajectory().trajectory();
if (chosen_trajectories.empty() ||
chosen_trajectories[0].trajectory_point().empty()) {
return;
}
const auto& vehicle_state = frame_->vehicle_state();
auto chart = debug_chart->mutable_planning_data()->add_chart();
auto chart_kappa = debug_chart->mutable_planning_data()->add_chart();
auto chart_theta = debug_chart->mutable_planning_data()->add_chart();
chart->set_title("Open Space Partitioned Trajectory");
chart_kappa->set_title("total kappa");
chart_theta->set_title("total theta");
auto* options = chart->mutable_options();
options->mutable_x()->set_label_string("x (meter)");
options->mutable_y()->set_label_string("y (meter)");
options->set_sync_xy_window_size(true);
options->set_aspect_ratio(0.9);
// Draw vehicle state
auto* adc_shape = chart->add_car();
adc_shape->set_x(vehicle_state.x());
adc_shape->set_y(vehicle_state.y());
adc_shape->set_heading(vehicle_state.heading());
adc_shape->set_label("ADV");
adc_shape->set_color("rgba(54, 162, 235, 1)");
// Draw the chosen trajectories
const auto& chosen_trajectory = chosen_trajectories[0];
auto* chosen_line = chart->add_line();
chosen_line->set_label("Chosen");
for (const auto& point : chosen_trajectory.trajectory_point()) {
auto* point_debug = chosen_line->add_point();
point_debug->set_x(point.path_point().x());
point_debug->set_y(point.path_point().y());
}
auto* chosen_properties = chosen_line->mutable_properties();
(*chosen_properties)["borderWidth"] = "2";
(*chosen_properties)["pointRadius"] = "0";
(*chosen_properties)["lineTension"] = "0";
(*chosen_properties)["fill"] = "false";
(*chosen_properties)["showLine"] = "true";
auto* theta_line = chart_theta->add_line();
auto* kappa_line = chart_kappa->add_line();
// Draw partitioned trajectories
size_t partitioned_trajectory_label = 0;
for (const auto& partitioned_trajectory :
open_space_debug.partitioned_trajectories().trajectory()) {
auto* partition_line = chart->add_line();
partition_line->set_label(
absl::StrCat("Partitioned ", partitioned_trajectory_label));
++partitioned_trajectory_label;
for (const auto& point : partitioned_trajectory.trajectory_point()) {
auto* point_debug = partition_line->add_point();
auto* point_theta = theta_line->add_point();
auto* point_kappa = kappa_line->add_point();
point_debug->set_x(point.path_point().x());
point_debug->set_y(point.path_point().y());
point_theta->set_x(point.relative_time());
point_kappa->set_x(point.relative_time());
point_theta->set_y(point.path_point().theta());
point_kappa->set_y(point.path_point().kappa());
}
auto* partition_properties = partition_line->mutable_properties();
(*partition_properties)["borderWidth"] = "2";
(*partition_properties)["pointRadius"] = "0";
(*partition_properties)["lineTension"] = "0";
(*partition_properties)["fill"] = "false";
(*partition_properties)["showLine"] = "true";
SetChartminmax(chart_kappa, "time", "total kappa");
SetChartminmax(chart_theta, "time", "total theta");
}
// Draw trajectory stitching point (line with only one point)
auto* stitching_line = chart->add_line();
stitching_line->set_label("TrajectoryStitchingPoint");
auto* trajectory_stitching_point = stitching_line->add_point();
trajectory_stitching_point->set_x(
open_space_debug.trajectory_stitching_point().path_point().x());
trajectory_stitching_point->set_y(
open_space_debug.trajectory_stitching_point().path_point().y());
// Set chartJS's dataset properties
auto* stitching_properties = stitching_line->mutable_properties();
(*stitching_properties)["borderWidth"] = "3";
(*stitching_properties)["pointRadius"] = "5";
(*stitching_properties)["lineTension"] = "0";
(*stitching_properties)["fill"] = "true";
(*stitching_properties)["showLine"] = "true";
// Draw fallback trajectory compared with the partitioned and potential
// collision_point (line with only one point)
if (open_space_debug.is_fallback_trajectory()) {
auto* collision_line = chart->add_line();
collision_line->set_label("FutureCollisionPoint");
auto* future_collision_point = collision_line->add_point();
future_collision_point->set_x(
open_space_debug.future_collision_point().path_point().x());
future_collision_point->set_y(
open_space_debug.future_collision_point().path_point().y());
// Set chartJS's dataset properties
auto* collision_properties = collision_line->mutable_properties();
(*collision_properties)["borderWidth"] = "3";
(*collision_properties)["pointRadius"] = "8";
(*collision_properties)["lineTension"] = "0";
(*collision_properties)["fill"] = "true";
(*stitching_properties)["showLine"] = "true";
(*stitching_properties)["pointStyle"] = "cross";
const auto& fallback_trajectories =
open_space_debug.fallback_trajectory().trajectory();
if (fallback_trajectories.empty() ||
fallback_trajectories[0].trajectory_point().empty()) {
return;
}
const auto& fallback_trajectory = fallback_trajectories[0];
// has to define chart boundary first
auto* fallback_line = chart->add_line();
fallback_line->set_label("Fallback");
for (const auto& point : fallback_trajectory.trajectory_point()) {
auto* point_debug = fallback_line->add_point();
point_debug->set_x(point.path_point().x());
point_debug->set_y(point.path_point().y());
}
// Set chartJS's dataset properties
auto* fallback_properties = fallback_line->mutable_properties();
(*fallback_properties)["borderWidth"] = "3";
(*fallback_properties)["pointRadius"] = "2";
(*fallback_properties)["lineTension"] = "0";
(*fallback_properties)["fill"] = "false";
(*fallback_properties)["showLine"] = "true";
}
}
void OnLanePlanning::AddStitchSpeedProfile(
planning_internal::Debug* debug_chart) {
if (!injector_->frame_history()->Latest()) {
AINFO << "Planning frame is empty!";
return;
}
// if open space info provider success run
if (!frame_->open_space_info().open_space_provider_success()) {
return;
}
auto chart = debug_chart->mutable_planning_data()->add_chart();
chart->set_title("Open Space Speed Plan Visualization");
auto* options = chart->mutable_options();
// options->mutable_x()->set_mid_value(Clock::NowInSeconds());
double xmin(std::numeric_limits<double>::max()),
xmax(std::numeric_limits<double>::lowest()),
ymin(std::numeric_limits<double>::max()),
ymax(std::numeric_limits<double>::lowest());
// auto smoothed_trajectory = open_space_debug.smoothed_trajectory();
auto* speed_profile = chart->add_line();
speed_profile->set_label("Speed Profile");
const auto& last_trajectory =
injector_->frame_history()->Latest()->current_frame_planned_trajectory();
for (const auto& point : last_trajectory.trajectory_point()) {
auto* point_debug = speed_profile->add_point();
point_debug->set_x(point.relative_time() +
last_trajectory.header().timestamp_sec());
point_debug->set_y(point.v());
if (point_debug->x() > xmax) xmax = point_debug->x();
if (point_debug->x() < xmin) xmin = point_debug->x();
if (point_debug->y() > ymax) ymax = point_debug->y();
if (point_debug->y() < ymin) ymin = point_debug->y();
}
options->mutable_x()->set_window_size(xmax - xmin);
options->mutable_x()->set_label_string("time (s)");
options->mutable_y()->set_min(ymin);
options->mutable_y()->set_max(ymax);
options->mutable_y()->set_label_string("speed (m/s)");
// Set chartJS's dataset properties
auto* speed_profile_properties = speed_profile->mutable_properties();
(*speed_profile_properties)["borderWidth"] = "2";
(*speed_profile_properties)["pointRadius"] = "0";
(*speed_profile_properties)["lineTension"] = "0";
(*speed_profile_properties)["fill"] = "false";
(*speed_profile_properties)["showLine"] = "true";
}
void OnLanePlanning::AddPublishedSpeed(const ADCTrajectory& trajectory_pb,
planning_internal::Debug* debug_chart) {
// if open space info provider success run
if (!frame_->open_space_info().open_space_provider_success()) {
return;
}
auto chart = debug_chart->mutable_planning_data()->add_chart();
chart->set_title("Speed Partition Visualization");
auto* options = chart->mutable_options();
// options->mutable_x()->set_mid_value(Clock::NowInSeconds());
// auto smoothed_trajectory = open_space_debug.smoothed_trajectory();
auto* speed_profile = chart->add_line();
speed_profile->set_label("Speed Profile");
double xmin(std::numeric_limits<double>::max()),
xmax(std::numeric_limits<double>::lowest()),
ymin(std::numeric_limits<double>::max()),
ymax(std::numeric_limits<double>::lowest());
for (const auto& point : trajectory_pb.trajectory_point()) {
auto* point_debug = speed_profile->add_point();
point_debug->set_x(point.relative_time() +
trajectory_pb.header().timestamp_sec());
if (trajectory_pb.gear() == canbus::Chassis::GEAR_DRIVE) {
point_debug->set_y(point.v());
}
if (trajectory_pb.gear() == canbus::Chassis::GEAR_REVERSE) {
point_debug->set_y(-point.v());
}
if (point_debug->x() > xmax) xmax = point_debug->x();
if (point_debug->x() < xmin) xmin = point_debug->x();
if (point_debug->y() > ymax) ymax = point_debug->y();
if (point_debug->y() < ymin) ymin = point_debug->y();
}
options->mutable_x()->set_window_size(xmax - xmin);
options->mutable_x()->set_label_string("time (s)");
options->mutable_y()->set_min(ymin);
options->mutable_y()->set_max(ymax);
options->mutable_y()->set_label_string("speed (m/s)");
// Set chartJS's dataset properties
auto* speed_profile_properties = speed_profile->mutable_properties();
(*speed_profile_properties)["borderWidth"] = "2";
(*speed_profile_properties)["pointRadius"] = "0";
(*speed_profile_properties)["lineTension"] = "0";
(*speed_profile_properties)["fill"] = "false";
(*speed_profile_properties)["showLine"] = "true";
auto* sliding_line = chart->add_line();
sliding_line->set_label("Time");
auto* point_debug_up = sliding_line->add_point();
point_debug_up->set_x(Clock::NowInSeconds());
point_debug_up->set_y(2.1);
auto* point_debug_down = sliding_line->add_point();
point_debug_down->set_x(Clock::NowInSeconds());
point_debug_down->set_y(-1.1);
// Set chartJS's dataset properties
auto* sliding_line_properties = sliding_line->mutable_properties();
(*sliding_line_properties)["borderWidth"] = "2";
(*sliding_line_properties)["pointRadius"] = "0";
(*sliding_line_properties)["lineTension"] = "0";
(*sliding_line_properties)["fill"] = "false";
(*sliding_line_properties)["showLine"] = "true";
}
VehicleState OnLanePlanning::AlignTimeStamp(const VehicleState& vehicle_state,
const double curr_timestamp) const {
// TODO(Jinyun): use the same method in trajectory stitching
// for forward prediction
auto future_xy = injector_->vehicle_state()->EstimateFuturePosition(
curr_timestamp - vehicle_state.timestamp());
VehicleState aligned_vehicle_state = vehicle_state;
aligned_vehicle_state.set_x(future_xy.x());
aligned_vehicle_state.set_y(future_xy.y());
aligned_vehicle_state.set_timestamp(curr_timestamp);
return aligned_vehicle_state;
}
void OnLanePlanning::AddPublishedAcceleration(
const ADCTrajectory& trajectory_pb, planning_internal::Debug* debug) {
// if open space info provider success run
if (!frame_->open_space_info().open_space_provider_success()) {
return;
}
double xmin(std::numeric_limits<double>::max()),
xmax(std::numeric_limits<double>::lowest()),
ymin(std::numeric_limits<double>::max()),
ymax(std::numeric_limits<double>::lowest());
auto chart = debug->mutable_planning_data()->add_chart();
chart->set_title("Acceleration Partition Visualization");
auto* options = chart->mutable_options();
// options->mutable_x()->set_mid_value(Clock::NowInSeconds());
auto* acceleration_profile = chart->add_line();
acceleration_profile->set_label("Acceleration Profile");
for (const auto& point : trajectory_pb.trajectory_point()) {
auto* point_debug = acceleration_profile->add_point();
point_debug->set_x(point.relative_time() +
trajectory_pb.header().timestamp_sec());
if (trajectory_pb.gear() == canbus::Chassis::GEAR_DRIVE)
point_debug->set_y(point.a());
if (trajectory_pb.gear() == canbus::Chassis::GEAR_REVERSE)
point_debug->set_y(-point.a());
if (point_debug->x() > xmax) xmax = point_debug->x();
if (point_debug->x() < xmin) xmin = point_debug->x();
if (point_debug->y() > ymax) ymax = point_debug->y();
if (point_debug->y() < ymin) ymin = point_debug->y();
}
options->mutable_x()->set_window_size(xmax - xmin);
options->mutable_x()->set_label_string("time (s)");
options->mutable_y()->set_min(ymin);
options->mutable_y()->set_max(ymax);
options->mutable_y()->set_label_string("acceleration (m/s)");
// Set chartJS's dataset properties
auto* acceleration_profile_properties =
acceleration_profile->mutable_properties();
(*acceleration_profile_properties)["borderWidth"] = "2";
(*acceleration_profile_properties)["pointRadius"] = "0";
(*acceleration_profile_properties)["lineTension"] = "0";
(*acceleration_profile_properties)["fill"] = "false";
(*acceleration_profile_properties)["showLine"] = "true";
auto* sliding_line = chart->add_line();
sliding_line->set_label("Time");
auto* point_debug_up = sliding_line->add_point();
point_debug_up->set_x(Clock::NowInSeconds());
point_debug_up->set_y(2.1);
auto* point_debug_down = sliding_line->add_point();
point_debug_down->set_x(Clock::NowInSeconds());
point_debug_down->set_y(-1.1);
// Set chartJS's dataset properties
auto* sliding_line_properties = sliding_line->mutable_properties();
(*sliding_line_properties)["borderWidth"] = "2";
(*sliding_line_properties)["pointRadius"] = "0";
(*sliding_line_properties)["lineTension"] = "0";
(*sliding_line_properties)["fill"] = "false";
(*sliding_line_properties)["showLine"] = "true";
}
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/planning_component.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include "cyber/class_loader/class_loader.h"
#include "cyber/component/component.h"
#include "cyber/message/raw_message.h"
#include "modules/common_msgs/chassis_msgs/chassis.pb.h"
#include "modules/common_msgs/localization_msgs/localization.pb.h"
#include "modules/common_msgs/perception_msgs/traffic_light_detection.pb.h"
#include "modules/planning/common/message_process.h"
#include "modules/planning/common/planning_gflags.h"
#include "modules/planning/planning_base.h"
#include "modules/planning/proto/learning_data.pb.h"
#include "modules/common_msgs/planning_msgs/pad_msg.pb.h"
#include "modules/common_msgs/planning_msgs/planning.pb.h"
#include "modules/planning/proto/planning_config.pb.h"
#include "modules/common_msgs/prediction_msgs/prediction_obstacle.pb.h"
#include "modules/common_msgs/routing_msgs/routing.pb.h"
#include "modules/common_msgs/storytelling_msgs/story.pb.h"
namespace apollo {
namespace planning {
class PlanningComponent final
: public cyber::Component<prediction::PredictionObstacles, canbus::Chassis,
localization::LocalizationEstimate> {
public:
PlanningComponent() = default;
~PlanningComponent() = default;
public:
bool Init() override;
bool Proc(const std::shared_ptr<prediction::PredictionObstacles>&
prediction_obstacles,
const std::shared_ptr<canbus::Chassis>& chassis,
const std::shared_ptr<localization::LocalizationEstimate>&
localization_estimate) override;
private:
void CheckRerouting();
bool CheckInput();
private:
std::shared_ptr<cyber::Reader<perception::TrafficLightDetection>>
traffic_light_reader_;
std::shared_ptr<cyber::Reader<routing::RoutingResponse>> routing_reader_;
std::shared_ptr<cyber::Reader<planning::PadMessage>> pad_msg_reader_;
std::shared_ptr<cyber::Reader<relative_map::MapMsg>> relative_map_reader_;
std::shared_ptr<cyber::Reader<storytelling::Stories>> story_telling_reader_;
std::shared_ptr<cyber::Writer<ADCTrajectory>> planning_writer_;
std::shared_ptr<cyber::Writer<routing::RoutingRequest>> rerouting_writer_;
std::shared_ptr<cyber::Writer<PlanningLearningData>>
planning_learning_data_writer_;
std::mutex mutex_;
perception::TrafficLightDetection traffic_light_;
routing::RoutingResponse routing_;
planning::PadMessage pad_msg_;
relative_map::MapMsg relative_map_;
storytelling::Stories stories_;
LocalView local_view_;
std::unique_ptr<PlanningBase> planning_base_;
std::shared_ptr<DependencyInjector> injector_;
PlanningConfig config_;
MessageProcess message_process_;
};
CYBER_REGISTER_COMPONENT(PlanningComponent)
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/navi_planning.h
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#pragma once
#include <memory>
#include <string>
#include <utility>
#include <vector>
#include "modules/common/util/future.h"
#include "modules/planning/planner/navi_planner_dispatcher.h"
#include "modules/planning/planner/planner_dispatcher.h"
#include "modules/planning/planning_base.h"
#include "modules/common_msgs/planning_msgs/pad_msg.pb.h"
/**
* @namespace apollo::planning
* @brief apollo::planning
*/
namespace apollo {
namespace planning {
/**
* @class planning
*
* @brief Planning module main class. It processes GPS and IMU as input,
* to generate planning info.
*/
class NaviPlanning : public PlanningBase {
public:
explicit NaviPlanning(const std::shared_ptr<DependencyInjector>& injector)
: PlanningBase(injector) {
planner_dispatcher_ = std::make_unique<NaviPlannerDispatcher>();
}
virtual ~NaviPlanning();
/**
* @brief Planning algorithm name.
*/
std::string Name() const override;
/**
* @brief module initialization function
* @return initialization status
*/
apollo::common::Status Init(const PlanningConfig& config) override;
/**
* @brief main logic of the planning module, runs periodically triggered by
* timer.
*/
void RunOnce(const LocalView& local_view,
ADCTrajectory* const trajectory_pb) override;
apollo::common::Status Plan(
const double current_time_stamp,
const std::vector<common::TrajectoryPoint>& stitching_trajectory,
ADCTrajectory* const trajectory) override;
private:
common::Status InitFrame(const uint32_t sequence_num,
const common::TrajectoryPoint& planning_start_point,
const common::VehicleState& vehicle_state);
bool CheckPlanningConfig(const PlanningConfig& config);
/**
* @brief make driving decisions by received planning pad msg
*/
void ProcessPadMsg(PadMessage::DrivingAction drvie_action);
/**
* @brief get the lane Id of the lane in which the vehicle is located
*/
std::string GetCurrentLaneId();
/**
* @brief get the left neighbors lane info of the lane which the vehicle is
*located
* @lane_info_group output left neighbors info which sorted from near to
*far
*/
void GetLeftNeighborLanesInfo(
std::vector<std::pair<std::string, double>>* const lane_info_group);
/**
* @brief get the right neighbors lane of the lane which the vehicle is
* located
* @lane_info_group output right neighbors info which sorted from near to
*far
*/
void GetRightNeighborLanesInfo(
std::vector<std::pair<std::string, double>>* const lane_info_group);
void ExportReferenceLineDebug(planning_internal::Debug* debug);
class VehicleConfig {
public:
double x_ = 0.0;
double y_ = 0.0;
double theta_ = 0.0;
bool is_valid_ = false;
};
VehicleConfig last_vehicle_config_;
VehicleConfig ComputeVehicleConfigFromLocalization(
const localization::LocalizationEstimate& localization) const;
std::string target_lane_id_;
std::unique_ptr<ReferenceLineProvider> reference_line_provider_;
};
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_binary", "cc_library")
load("//tools/install:install.bzl", "install", "install_files", "install_src_files")
load("//tools:cpplint.bzl", "cpplint")
load("//third_party/gpus:common.bzl", "if_gpu")
package(default_visibility = ["//visibility:public"])
install(
name = "planning_testdata_install",
data_dest = if_gpu(
"planning-gpu/addition_data",
"planning/addition_data"
),
data = [":planning_testdata"],
)
cc_binary(
name = "libplanning_component.so",
linkshared = True,
linkstatic = True,
deps = [":planning_component_lib"],
)
cc_library(
name = "planning_component_lib",
srcs = ["planning_component.cc"],
hdrs = ["planning_component.h"],
copts = [
"-DMODULE_NAME=\\\"planning\\\"",
],
deps = [
":navi_planning",
":on_lane_planning",
"//cyber",
"//modules/common/adapters:adapter_gflags",
"//modules/common/util:util_tool",
"//modules/common_msgs/localization_msgs:localization_cc_proto",
"//modules/common_msgs/planning_msgs:navigation_cc_proto",
"//modules/common_msgs/perception_msgs:traffic_light_detection_cc_proto",
"//modules/planning/common:history",
"//modules/planning/common:message_process",
"//modules/common_msgs/planning_msgs:planning_cc_proto",
"//modules/common_msgs/prediction_msgs:prediction_obstacle_cc_proto",
"//modules/common_msgs/storytelling_msgs:story_cc_proto",
],
alwayslink = True,
)
cc_library(
name = "planning_base",
srcs = ["planning_base.cc"],
hdrs = ["planning_base.h"],
copts = [
"-fopenmp",
"-DMODULE_NAME=\\\"planning\\\""
],
deps = [
"//cyber",
"//modules/common_msgs/basic_msgs:pnc_point_cc_proto",
"//modules/common_msgs/chassis_msgs:chassis_cc_proto",
"//modules/common_msgs/dreamview_msgs:chart_cc_proto",
"//modules/common_msgs/localization_msgs:localization_cc_proto",
"//modules/common_msgs/perception_msgs:traffic_light_detection_cc_proto",
"//modules/common_msgs/planning_msgs:planning_cc_proto",
"//modules/common_msgs/planning_msgs:planning_internal_cc_proto",
"//modules/common_msgs/prediction_msgs:prediction_obstacle_cc_proto",
"//modules/common_msgs/routing_msgs:routing_cc_proto",
"//modules/common/status",
"//modules/common/vehicle_state:vehicle_state_provider",
"//modules/map/hdmap:hdmap_util",
"//modules/map/hdmap",
"//modules/planning/common:dependency_injector",
"//modules/planning/common:frame",
"//modules/planning/common:local_view",
"//modules/planning/common:planning_context",
"//modules/planning/common:planning_gflags",
"//modules/planning/common/trajectory:publishable_trajectory",
"//modules/planning/planner:planner_dispatcher",
"//modules/planning/planner",
"//modules/planning/proto:planning_config_cc_proto",
"//modules/planning/proto:traffic_rule_config_cc_proto",
"//modules/planning/tasks:task_factory",
],
)
cc_library(
name = "navi_planning",
srcs = ["navi_planning.cc"],
hdrs = ["navi_planning.h"],
copts = [
"-fopenmp",
"-DMODULE_NAME=\\\"planning\\\""
],
deps = [
":planning_base",
"//cyber",
"//modules/common_msgs/planning_msgs:pad_msg_cc_proto",
"//modules/common/math",
"//modules/common/util:util_tool",
"//modules/common/vehicle_state:vehicle_state_provider",
"//modules/map/hdmap:hdmap_util",
"//modules/planning/common:ego_info",
"//modules/planning/common:history",
"//modules/planning/common:planning_context",
"//modules/planning/common:planning_gflags",
"//modules/planning/common:trajectory_stitcher",
"//modules/planning/common/util:util_lib",
"//modules/planning/planner:planner_dispatcher",
"//modules/planning/planner/navi:navi_planner",
"//modules/planning/planner/rtk:rtk_planner",
"//modules/planning/reference_line:reference_line_provider",
"//modules/planning/traffic_rules:traffic_decider",
"@com_google_protobuf//:protobuf",
],
)
cc_library(
name = "on_lane_planning",
srcs = ["on_lane_planning.cc"],
hdrs = ["on_lane_planning.h"],
copts = [
"-fopenmp",
"-DMODULE_NAME=\\\"planning\\\"",
],
deps = [
":planning_base",
"//cyber",
"//modules/common_msgs/planning_msgs:planning_internal_cc_proto",
"//modules/common_msgs/routing_msgs:routing_cc_proto",
"//modules/common/math",
"//modules/common/vehicle_state:vehicle_state_provider",
"//modules/map/hdmap:hdmap_util",
"//modules/planning/common:ego_info",
"//modules/planning/common:history",
"//modules/planning/common:planning_context",
"//modules/planning/common:planning_gflags",
"//modules/planning/common:trajectory_stitcher",
"//modules/planning/common/smoothers:smoother",
"//modules/planning/common/util:util_lib",
"//modules/planning/learning_based/img_feature_renderer:birdview_img_feature_renderer",
"//modules/planning/planner:planner_dispatcher",
"//modules/planning/planner/rtk:rtk_planner",
"//modules/planning/proto:planning_semantic_map_config_cc_proto",
"//modules/planning/reference_line:reference_line_provider",
"//modules/planning/tasks:task_factory",
"//modules/planning/traffic_rules:traffic_decider",
"@com_google_absl//:absl",
"@com_google_googletest//:gtest_main",
],
)
filegroup(
name = "planning_testdata",
srcs = glob([
"testdata/**",
]),
)
filegroup(
name = "planning_conf",
srcs = glob([
"conf/**",
]),
)
filegroup(
name = "runtime_data",
srcs = glob([
"dag/*.dag",
"launch/*.launch",
]) + [":planning_conf"],
)
install(
name = "install",
data_dest = if_gpu(
"planning-gpu",
"planning"
),
library_dest = if_gpu(
"planning-gpu/lib",
"planning/lib"
),
data = [
":runtime_data",
] + if_gpu(
["planning-gpu.BUILD", "cyberfile_gpu.xml",],
["planning.BUILD", "cyberfile_cpu.xml",]
),
rename= if_gpu(
{"planning-gpu/cyberfile_gpu.xml": "cyberfile.xml"},
{"planning/cyberfile_cpu.xml": "cyberfile.xml"}
),
targets = [
":libplanning_component.so",
],
deps = [
":pb_planning",
":planning_testdata_install",
"//modules/planning/proto:py_pb_planning",
"//modules/planning/proto:pb_hdrs_planning",
],
)
install_files(
name = "pb_planning",
dest = if_gpu(
"planning-gpu",
"planning"
),
files = [
"//modules/planning/proto:auto_tuning_raw_feature_py_pb2",
"//modules/common_msgs/planning_msgs:decision_py_pb2",
"//modules/planning/proto:ipopt_return_status_py_pb2",
"//modules/planning/proto:lattice_structure_py_pb2",
"//modules/planning/proto:learning_data_py_pb2",
"//modules/common_msgs/control_msgs:pad_msg_py_pb2",
"//modules/common_msgs/planning_msgs:planning_internal_py_pb2",
"//modules/common_msgs/planning_msgs:planning_py_pb2",
"//modules/planning/proto:planning_semantic_map_config_py_pb2",
"//modules/planning/proto:planning_stats_py_pb2",
"//modules/planning/proto:planning_status_py_pb2",
"//modules/planning/proto:reference_line_smoother_config_py_pb2",
"//modules/common_msgs/planning_msgs:sl_boundary_py_pb2",
"//modules/planning/proto:st_drivable_boundary_py_pb2",
"//modules/planning/proto:traffic_rule_config_py_pb2",
"//modules/planning/proto/math:cos_theta_smoother_config_py_pb2",
"//modules/planning/proto/math:qp_problem_py_pb2",
],
)
install_src_files(
name = "install_src",
deps = [
":install_planning_src",
":install_planning_hdrs"
],
)
install_src_files(
name = "install_planning_src",
src_dir = ["."],
dest = if_gpu(
"planning-gpu/src",
"planning/src"
),
filter = "*",
)
install_src_files(
name = "install_planning_hdrs",
src_dir = ["."],
dest = if_gpu(
"planning-gpu/include",
"planning/include"
),
filter = "*.h",
)
install(
name = "pb_hdrs",
data_dest = "planning/include",
data = [
"//modules/planning/proto:st_drivable_boundary_py_pb2",
"//modules/planning/proto:planning_stats_py_pb2",
"//modules/planning/proto:planning_semantic_map_config_py_pb2",
"//modules/planning/proto:traffic_rule_config_py_pb2",
"//modules/planning/proto:planning_status_py_pb2",
"//modules/planning/proto:lattice_structure_py_pb2",
"//modules/planning/proto:learning_data_py_pb2",
"//modules/planning/proto:auto_tuning_model_input_py_pb2",
"//modules/planning/proto:auto_tuning_raw_feature_py_pb2",
"//modules/planning/proto:reference_line_smoother_config_py_pb2",
"//modules/planning/proto:ipopt_return_status_py_pb2",
"//modules/planning/proto/math:fem_pos_deviation_smoother_config_py_pb2",
"//modules/planning/proto:open_space_task_config_py_pb2",
"//modules/planning/proto:planner_open_space_config_py_pb2",
"//modules/planning/proto:task_config_py_pb2",
"//modules/planning/proto:planning_config_py_pb2",
],
)
cpplint()
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/planning_base.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/planning/planning_base.h"
#include "cyber/time/clock.h"
#include "modules/common_msgs/planning_msgs/planning_internal.pb.h"
#include "modules/map/hdmap/hdmap_util.h"
#include "modules/planning/common/planning_context.h"
#include "modules/planning/common/planning_gflags.h"
#include "modules/planning/tasks/task_factory.h"
namespace apollo {
namespace planning {
using apollo::common::Status;
PlanningBase::PlanningBase(const std::shared_ptr<DependencyInjector>& injector)
: injector_(injector) {}
PlanningBase::~PlanningBase() {}
Status PlanningBase::Init(const PlanningConfig& config) {
injector_->planning_context()->Init();
TaskFactory::Init(config, injector_);
return Status::OK();
}
void PlanningBase::FillPlanningPb(const double timestamp,
ADCTrajectory* const trajectory_pb) {
trajectory_pb->mutable_header()->set_timestamp_sec(timestamp);
if (local_view_.prediction_obstacles->has_header()) {
trajectory_pb->mutable_header()->set_lidar_timestamp(
local_view_.prediction_obstacles->header().lidar_timestamp());
trajectory_pb->mutable_header()->set_camera_timestamp(
local_view_.prediction_obstacles->header().camera_timestamp());
trajectory_pb->mutable_header()->set_radar_timestamp(
local_view_.prediction_obstacles->header().radar_timestamp());
}
trajectory_pb->mutable_routing_header()->CopyFrom(
local_view_.routing->header());
}
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/navi_planning.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/planning/navi_planning.h"
#include <algorithm>
#include <list>
#include <map>
#include "cyber/common/file.h"
#include "cyber/time/clock.h"
#include "google/protobuf/repeated_field.h"
#include "modules/common/math/quaternion.h"
#include "modules/common/vehicle_state/vehicle_state_provider.h"
#include "modules/map/hdmap/hdmap_util.h"
#include "modules/planning/common/ego_info.h"
#include "modules/planning/common/history.h"
#include "modules/planning/common/planning_context.h"
#include "modules/planning/common/planning_gflags.h"
#include "modules/planning/common/trajectory_stitcher.h"
#include "modules/planning/common/util/util.h"
#include "modules/planning/planner/navi/navi_planner.h"
#include "modules/planning/planner/rtk/rtk_replay_planner.h"
#include "modules/planning/reference_line/reference_line_provider.h"
#include "modules/planning/traffic_rules/traffic_decider.h"
namespace apollo {
namespace planning {
using apollo::common::ErrorCode;
using apollo::common::Status;
using apollo::common::TrajectoryPoint;
using apollo::common::VehicleState;
using apollo::common::VehicleStateProvider;
using apollo::cyber::Clock;
using apollo::hdmap::HDMapUtil;
NaviPlanning::~NaviPlanning() {
last_publishable_trajectory_.reset(nullptr);
frame_.reset(nullptr);
planner_.reset(nullptr);
injector_->frame_history()->Clear();
injector_->history()->Clear();
injector_->planning_context()->mutable_planning_status()->Clear();
}
std::string NaviPlanning::Name() const { return "navi_planning"; }
Status NaviPlanning::Init(const PlanningConfig& config) {
config_ = config;
if (!CheckPlanningConfig(config_)) {
return Status(ErrorCode::PLANNING_ERROR,
"planning config error: " + config_.DebugString());
}
PlanningBase::Init(config_);
planner_dispatcher_->Init();
ACHECK(apollo::cyber::common::GetProtoFromFile(
FLAGS_traffic_rule_config_filename, &traffic_rule_configs_))
<< "Failed to load traffic rule config file "
<< FLAGS_traffic_rule_config_filename;
// clear planning history
injector_->history()->Clear();
// clear planning status
injector_->planning_context()->mutable_planning_status()->Clear();
planner_ = planner_dispatcher_->DispatchPlanner(config_, injector_);
if (!planner_) {
return Status(
ErrorCode::PLANNING_ERROR,
"planning is not initialized with config : " + config_.DebugString());
}
return planner_->Init(config_);
}
Status NaviPlanning::InitFrame(const uint32_t sequence_num,
const TrajectoryPoint& planning_start_point,
const VehicleState& vehicle_state) {
frame_.reset(new Frame(sequence_num, local_view_, planning_start_point,
vehicle_state, reference_line_provider_.get()));
std::list<ReferenceLine> reference_lines;
std::list<hdmap::RouteSegments> segments;
if (!reference_line_provider_->GetReferenceLines(&reference_lines,
&segments)) {
const std::string msg = "Failed to create reference line";
AERROR << msg;
return Status(ErrorCode::PLANNING_ERROR, msg);
}
auto status = frame_->Init(
injector_->vehicle_state(), reference_lines, segments,
reference_line_provider_->FutureRouteWaypoints(), injector_->ego_info());
if (!status.ok()) {
AERROR << "failed to init frame:" << status.ToString();
return status;
}
return Status::OK();
}
void NaviPlanning::RunOnce(const LocalView& local_view,
ADCTrajectory* const trajectory_pb) {
local_view_ = local_view;
const double start_timestamp = Clock::NowInSeconds();
// recreate reference line provider in every cycle
hdmap_ = HDMapUtil::BaseMapPtr(*local_view.relative_map);
// Prefer "std::make_unique" to direct use of "new".
// Refer to "https://herbsutter.com/gotw/_102/" for details.
reference_line_provider_ = std::make_unique<ReferenceLineProvider>(
injector_->vehicle_state(), hdmap_, local_view_.relative_map);
// localization
ADEBUG << "Get localization: "
<< local_view_.localization_estimate->DebugString();
// chassis
ADEBUG << "Get chassis: " << local_view_.chassis->DebugString();
Status status = injector_->vehicle_state()->Update(
*local_view_.localization_estimate, *local_view_.chassis);
auto vehicle_config =
ComputeVehicleConfigFromLocalization(*local_view_.localization_estimate);
if (last_vehicle_config_.is_valid_ && vehicle_config.is_valid_) {
auto x_diff_map = vehicle_config.x_ - last_vehicle_config_.x_;
auto y_diff_map = vehicle_config.y_ - last_vehicle_config_.y_;
auto cos_map_veh = std::cos(last_vehicle_config_.theta_);
auto sin_map_veh = std::sin(last_vehicle_config_.theta_);
auto x_diff_veh = cos_map_veh * x_diff_map + sin_map_veh * y_diff_map;
auto y_diff_veh = -sin_map_veh * x_diff_map + cos_map_veh * y_diff_map;
auto theta_diff = vehicle_config.theta_ - last_vehicle_config_.theta_;
TrajectoryStitcher::TransformLastPublishedTrajectory(
x_diff_veh, y_diff_veh, theta_diff, last_publishable_trajectory_.get());
}
last_vehicle_config_ = vehicle_config;
VehicleState vehicle_state = injector_->vehicle_state()->vehicle_state();
// estimate (x, y) at current timestamp
// This estimate is only valid if the current time and vehicle state timestamp
// differs only a small amount (20ms). When the different is too large, the
// estimation is invalid.
DCHECK_GE(start_timestamp, vehicle_state.timestamp());
if (start_timestamp - vehicle_state.timestamp() <
FLAGS_message_latency_threshold) {
auto future_xy = injector_->vehicle_state()->EstimateFuturePosition(
start_timestamp - vehicle_state.timestamp());
vehicle_state.set_x(future_xy.x());
vehicle_state.set_y(future_xy.y());
vehicle_state.set_timestamp(start_timestamp);
}
auto* not_ready = trajectory_pb->mutable_decision()
->mutable_main_decision()
->mutable_not_ready();
if (!status.ok() || !util::IsVehicleStateValid(vehicle_state)) {
const std::string msg = "Update VehicleStateProvider failed";
AERROR << msg;
not_ready->set_reason(msg);
status.Save(trajectory_pb->mutable_header()->mutable_status());
// TODO(all): integrate reverse gear
trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, trajectory_pb);
return;
}
const double planning_cycle_time = 1.0 / FLAGS_planning_loop_rate;
std::vector<TrajectoryPoint> stitching_trajectory;
std::string replan_reason;
stitching_trajectory = TrajectoryStitcher::ComputeStitchingTrajectory(
vehicle_state, start_timestamp, planning_cycle_time,
FLAGS_trajectory_stitching_preserved_length, true,
last_publishable_trajectory_.get(), &replan_reason);
const uint32_t frame_num = static_cast<uint32_t>(seq_num_++);
status = InitFrame(frame_num, stitching_trajectory.back(), vehicle_state);
if (!frame_) {
const std::string msg = "Failed to init frame";
AERROR << msg;
not_ready->set_reason(msg);
status.Save(trajectory_pb->mutable_header()->mutable_status());
// TODO(all): integrate reverse gear
trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, trajectory_pb);
return;
}
injector_->ego_info()->Update(stitching_trajectory.back(), vehicle_state);
if (FLAGS_enable_record_debug) {
frame_->RecordInputDebug(trajectory_pb->mutable_debug());
}
trajectory_pb->mutable_latency_stats()->set_init_frame_time_ms(
Clock::NowInSeconds() - start_timestamp);
if (!status.ok()) {
AERROR << status.ToString();
if (FLAGS_publish_estop) {
// Because the function "Control::ProduceControlCommand()" checks the
// "estop" signal with the following line (Line 170 in control.cc):
// estop_ = estop_ || trajectory_.estop().is_estop();
// we should add more information to ensure the estop being triggered.
ADCTrajectory estop_trajectory;
EStop* estop = estop_trajectory.mutable_estop();
estop->set_is_estop(true);
estop->set_reason(status.error_message());
status.Save(estop_trajectory.mutable_header()->mutable_status());
// TODO(all): integrate reverse gear
trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, &estop_trajectory);
} else {
trajectory_pb->mutable_decision()
->mutable_main_decision()
->mutable_not_ready()
->set_reason(status.ToString());
status.Save(trajectory_pb->mutable_header()->mutable_status());
// TODO(all): integrate reverse gear
trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, trajectory_pb);
}
frame_->set_current_frame_planned_trajectory(*trajectory_pb);
auto seq_num = frame_->SequenceNum();
injector_->frame_history()->Add(seq_num, std::move(frame_));
return;
}
// Use planning pad message to make driving decisions
if (FLAGS_enable_planning_pad_msg) {
const auto& pad_msg_driving_action = frame_->GetPadMsgDrivingAction();
ProcessPadMsg(pad_msg_driving_action);
}
for (auto& ref_line_info : *frame_->mutable_reference_line_info()) {
TrafficDecider traffic_decider;
traffic_decider.Init(traffic_rule_configs_);
auto traffic_status =
traffic_decider.Execute(frame_.get(), &ref_line_info, injector_);
if (!traffic_status.ok() || !ref_line_info.IsDrivable()) {
ref_line_info.SetDrivable(false);
AWARN << "Reference line " << ref_line_info.Lanes().Id()
<< " traffic decider failed";
continue;
}
}
status = Plan(start_timestamp, stitching_trajectory, trajectory_pb);
const auto time_diff_ms =
(Clock::NowInSeconds() - start_timestamp) * 1000;
ADEBUG << "total planning time spend: " << time_diff_ms << " ms.";
trajectory_pb->mutable_latency_stats()->set_total_time_ms(time_diff_ms);
ADEBUG << "Planning latency: "
<< trajectory_pb->latency_stats().DebugString();
auto* ref_line_task =
trajectory_pb->mutable_latency_stats()->add_task_stats();
ref_line_task->set_time_ms(reference_line_provider_->LastTimeDelay() *
1000.0);
ref_line_task->set_name("ReferenceLineProvider");
if (!status.ok()) {
status.Save(trajectory_pb->mutable_header()->mutable_status());
AERROR << "Planning failed:" << status.ToString();
if (FLAGS_publish_estop) {
AERROR << "Planning failed and set estop";
// Because the function "Control::ProduceControlCommand()" checks the
// "estop" signal with the following line (Line 170 in control.cc):
// estop_ = estop_ || trajectory_.estop().is_estop();
// we should add more information to ensure the estop being triggered.
EStop* estop = trajectory_pb->mutable_estop();
estop->set_is_estop(true);
estop->set_reason(status.error_message());
}
}
trajectory_pb->set_is_replan(stitching_trajectory.size() == 1);
// TODO(all): integrate reverse gear
trajectory_pb->set_gear(canbus::Chassis::GEAR_DRIVE);
FillPlanningPb(start_timestamp, trajectory_pb);
ADEBUG << "Planning pb:" << trajectory_pb->header().DebugString();
auto seq_num = frame_->SequenceNum();
injector_->frame_history()->Add(seq_num, std::move(frame_));
}
void NaviPlanning::ProcessPadMsg(PadMessage::DrivingAction drvie_action) {
if (config_.has_navigation_planning_config()) {
std::map<std::string, uint32_t> lane_id_to_priority;
auto& ref_line_info_group = *frame_->mutable_reference_line_info();
if (drvie_action != PadMessage::NONE) {
using LaneInfoPair = std::pair<std::string, double>;
std::string current_lane_id;
switch (drvie_action) {
case PadMessage::FOLLOW: {
AINFO << "Received follow drive action";
std::string current_lane_id = GetCurrentLaneId();
if (!current_lane_id.empty()) {
target_lane_id_ = current_lane_id;
}
break;
}
case PadMessage::CHANGE_LEFT: {
AINFO << "Received change left lane drive action";
std::vector<LaneInfoPair> lane_info_group;
GetLeftNeighborLanesInfo(&lane_info_group);
if (!lane_info_group.empty()) {
target_lane_id_ = lane_info_group.front().first;
}
break;
}
case PadMessage::CHANGE_RIGHT: {
AINFO << "Received change right lane drive action";
std::vector<LaneInfoPair> lane_info_group;
GetRightNeighborLanesInfo(&lane_info_group);
if (!lane_info_group.empty()) {
target_lane_id_ = lane_info_group.front().first;
}
break;
}
case PadMessage::PULL_OVER: {
AINFO << "Received pull over drive action";
// to do
break;
}
case PadMessage::STOP: {
AINFO << "Received stop drive action";
// to do
break;
}
default: {
AWARN << "Received undefined drive action.";
break;
}
}
}
if (!target_lane_id_.empty()) {
static constexpr uint32_t KTargetRefLinePriority = 0;
static constexpr uint32_t kOtherRefLinePriority = 10;
for (auto& ref_line_info : ref_line_info_group) {
auto lane_id = ref_line_info.Lanes().Id();
ADEBUG << "lane_id : " << lane_id;
lane_id_to_priority[lane_id] = kOtherRefLinePriority;
if (lane_id == target_lane_id_) {
lane_id_to_priority[lane_id] = KTargetRefLinePriority;
ADEBUG << "target lane_id : " << lane_id;
}
}
frame_->UpdateReferenceLinePriority(lane_id_to_priority);
}
}
// other planner to do
}
std::string NaviPlanning::GetCurrentLaneId() {
auto& ref_line_info_group = *frame_->mutable_reference_line_info();
const auto& vehicle_state = frame_->vehicle_state();
common::math::Vec2d adc_position(vehicle_state.x(), vehicle_state.y());
std::string current_lane_id;
for (auto& ref_line_info : ref_line_info_group) {
auto lane_id = ref_line_info.Lanes().Id();
auto& ref_line = ref_line_info.reference_line();
if (ref_line.IsOnLane(adc_position)) {
current_lane_id = lane_id;
}
}
return current_lane_id;
}
void NaviPlanning::GetLeftNeighborLanesInfo(
std::vector<std::pair<std::string, double>>* const lane_info_group) {
auto& ref_line_info_group = *frame_->mutable_reference_line_info();
const auto& vehicle_state = frame_->vehicle_state();
for (auto& ref_line_info : ref_line_info_group) {
common::math::Vec2d adc_position(vehicle_state.x(), vehicle_state.y());
auto& ref_line = ref_line_info.reference_line();
if (ref_line.IsOnLane(adc_position)) {
continue;
}
auto lane_id = ref_line_info.Lanes().Id();
auto ref_point =
ref_line.GetReferencePoint(vehicle_state.x(), vehicle_state.y());
double y = ref_point.y();
// in FLU positive on the left
if (y > 0.0) {
lane_info_group->emplace_back(lane_id, y);
}
}
// sort neighbor lanes from near to far
using LaneInfoPair = std::pair<std::string, double>;
std::sort(lane_info_group->begin(), lane_info_group->end(),
[](const LaneInfoPair& left, const LaneInfoPair& right) {
return left.second < right.second;
});
}
void NaviPlanning::GetRightNeighborLanesInfo(
std::vector<std::pair<std::string, double>>* const lane_info_group) {
auto& ref_line_info_group = *frame_->mutable_reference_line_info();
const auto& vehicle_state = frame_->vehicle_state();
for (auto& ref_line_info : ref_line_info_group) {
common::math::Vec2d adc_position(vehicle_state.x(), vehicle_state.y());
auto& ref_line = ref_line_info.reference_line();
if (ref_line.IsOnLane(adc_position)) {
continue;
}
auto lane_id = ref_line_info.Lanes().Id();
auto ref_point =
ref_line.GetReferencePoint(vehicle_state.x(), vehicle_state.y());
double y = ref_point.y();
// in FLU negative on the right
if (y < 0.0) {
lane_info_group->emplace_back(lane_id, y);
}
}
// sort neighbor lanes from near to far
using LaneInfoPair = std::pair<std::string, double>;
std::sort(lane_info_group->begin(), lane_info_group->end(),
[](const LaneInfoPair& left, const LaneInfoPair& right) {
return left.second > right.second;
});
}
void NaviPlanning::ExportReferenceLineDebug(planning_internal::Debug* debug) {
if (!FLAGS_enable_record_debug) {
return;
}
for (auto& reference_line_info : *frame_->mutable_reference_line_info()) {
auto rl_debug = debug->mutable_planning_data()->add_reference_line();
rl_debug->set_id(reference_line_info.Lanes().Id());
rl_debug->set_length(reference_line_info.reference_line().Length());
rl_debug->set_cost(reference_line_info.Cost());
rl_debug->set_is_change_lane_path(reference_line_info.IsChangeLanePath());
rl_debug->set_is_drivable(reference_line_info.IsDrivable());
rl_debug->set_is_protected(reference_line_info.GetRightOfWayStatus() ==
ADCTrajectory::PROTECTED);
}
}
Status NaviPlanning::Plan(
const double current_time_stamp,
const std::vector<TrajectoryPoint>& stitching_trajectory,
ADCTrajectory* const trajectory_pb) {
auto* ptr_debug = trajectory_pb->mutable_debug();
if (FLAGS_enable_record_debug) {
ptr_debug->mutable_planning_data()->mutable_init_point()->CopyFrom(
stitching_trajectory.back());
}
auto status =
planner_->Plan(stitching_trajectory.back(), frame_.get(), trajectory_pb);
ExportReferenceLineDebug(ptr_debug);
const auto* best_ref_info = frame_->FindDriveReferenceLineInfo();
if (!best_ref_info) {
const std::string msg = "planner failed to make a driving plan";
AERROR << msg;
if (last_publishable_trajectory_) {
last_publishable_trajectory_->Clear();
}
return Status(ErrorCode::PLANNING_ERROR, msg);
}
ptr_debug->MergeFrom(best_ref_info->debug());
trajectory_pb->mutable_latency_stats()->MergeFrom(
best_ref_info->latency_stats());
// set right of way status
trajectory_pb->set_right_of_way_status(best_ref_info->GetRightOfWayStatus());
for (const auto& id : best_ref_info->TargetLaneId()) {
trajectory_pb->add_lane_id()->CopyFrom(id);
}
best_ref_info->ExportDecision(trajectory_pb->mutable_decision(),
injector_->planning_context());
// Add debug information.
if (FLAGS_enable_record_debug) {
auto* reference_line = ptr_debug->mutable_planning_data()->add_path();
reference_line->set_name("planning_reference_line");
const auto& reference_points =
best_ref_info->reference_line().reference_points();
double s = 0.0;
double prev_x = 0.0;
double prev_y = 0.0;
bool empty_path = true;
for (const auto& reference_point : reference_points) {
auto* path_point = reference_line->add_path_point();
path_point->set_x(reference_point.x());
path_point->set_y(reference_point.y());
path_point->set_theta(reference_point.heading());
path_point->set_kappa(reference_point.kappa());
path_point->set_dkappa(reference_point.dkappa());
if (empty_path) {
path_point->set_s(0.0);
empty_path = false;
} else {
double dx = reference_point.x() - prev_x;
double dy = reference_point.y() - prev_y;
s += std::hypot(dx, dy);
path_point->set_s(s);
}
prev_x = reference_point.x();
prev_y = reference_point.y();
}
}
last_publishable_trajectory_.reset(new PublishableTrajectory(
current_time_stamp, best_ref_info->trajectory()));
ADEBUG << "current_time_stamp: " << current_time_stamp;
// Navi Planner doesn't need to stitch the last path planning
// trajectory.Otherwise, it will cause the Dreamview planning track to display
// flashing or bouncing
// TODO(Yifei): remove this if navi-planner doesn't need stitching
/**
if (FLAGS_enable_stitch_last_trajectory) {
last_publishable_trajectory_->PrependTrajectoryPoints(
std::vector<TrajectoryPoint>(stitching_trajectory.begin(),
stitching_trajectory.end() - 1));
}
**/
for (size_t i = 0; i < last_publishable_trajectory_->NumOfPoints(); ++i) {
if (last_publishable_trajectory_->TrajectoryPointAt(i).relative_time() >
FLAGS_trajectory_time_high_density_period) {
break;
}
ADEBUG << last_publishable_trajectory_->TrajectoryPointAt(i)
.ShortDebugString();
}
last_publishable_trajectory_->PopulateTrajectoryProtobuf(trajectory_pb);
best_ref_info->ExportEngageAdvice(trajectory_pb->mutable_engage_advice(),
injector_->planning_context());
return status;
}
/*void NaviPlanning::Stop() {
AWARN << "Planning Stop is called";
last_publishable_trajectory_.reset(nullptr);
frame_.reset(nullptr);
planner_.reset(nullptr);
frame_history_->Clear();
injector_->planning()->mutable_planning_status()->Clear();
}*/
NaviPlanning::VehicleConfig NaviPlanning::ComputeVehicleConfigFromLocalization(
const localization::LocalizationEstimate& localization) const {
NaviPlanning::VehicleConfig vehicle_config;
if (!localization.pose().has_position()) {
return vehicle_config;
}
vehicle_config.x_ = localization.pose().position().x();
vehicle_config.y_ = localization.pose().position().y();
const auto& orientation = localization.pose().orientation();
if (localization.pose().has_heading()) {
vehicle_config.theta_ = localization.pose().heading();
} else {
vehicle_config.theta_ = common::math::QuaternionToHeading(
orientation.qw(), orientation.qx(), orientation.qy(), orientation.qz());
}
vehicle_config.is_valid_ = true;
return vehicle_config;
}
bool NaviPlanning::CheckPlanningConfig(const PlanningConfig& config) {
if (!config.has_navigation_planning_config()) {
return false;
}
// TODO(All): check other config params
return true;
}
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/planning_component.cc
|
/******************************************************************************
* Copyright 2018 The Apollo Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*****************************************************************************/
#include "modules/planning/planning_component.h"
#include "cyber/common/file.h"
#include "modules/common/adapters/adapter_gflags.h"
#include "modules/common/configs/config_gflags.h"
#include "modules/common/util/message_util.h"
#include "modules/common/util/util.h"
#include "modules/map/hdmap/hdmap_util.h"
#include "modules/map/pnc_map/pnc_map.h"
#include "modules/planning/common/history.h"
#include "modules/planning/common/planning_context.h"
#include "modules/planning/navi_planning.h"
#include "modules/planning/on_lane_planning.h"
namespace apollo {
namespace planning {
using apollo::cyber::ComponentBase;
using apollo::hdmap::HDMapUtil;
using apollo::perception::TrafficLightDetection;
using apollo::relative_map::MapMsg;
using apollo::routing::RoutingRequest;
using apollo::routing::RoutingResponse;
using apollo::storytelling::Stories;
bool PlanningComponent::Init() {
injector_ = std::make_shared<DependencyInjector>();
if (FLAGS_use_navigation_mode) {
planning_base_ = std::make_unique<NaviPlanning>(injector_);
} else {
planning_base_ = std::make_unique<OnLanePlanning>(injector_);
}
ACHECK(ComponentBase::GetProtoConfig(&config_))
<< "failed to load planning config file "
<< ComponentBase::ConfigFilePath();
if (FLAGS_planning_offline_learning ||
config_.learning_mode() != PlanningConfig::NO_LEARNING) {
if (!message_process_.Init(config_, injector_)) {
AERROR << "failed to init MessageProcess";
return false;
}
}
planning_base_->Init(config_);
routing_reader_ = node_->CreateReader<RoutingResponse>(
config_.topic_config().routing_response_topic(),
[this](const std::shared_ptr<RoutingResponse>& routing) {
AINFO << "Received routing data: run routing callback."
<< routing->header().DebugString();
std::lock_guard<std::mutex> lock(mutex_);
routing_.CopyFrom(*routing);
});
traffic_light_reader_ = node_->CreateReader<TrafficLightDetection>(
config_.topic_config().traffic_light_detection_topic(),
[this](const std::shared_ptr<TrafficLightDetection>& traffic_light) {
ADEBUG << "Received traffic light data: run traffic light callback.";
std::lock_guard<std::mutex> lock(mutex_);
traffic_light_.CopyFrom(*traffic_light);
});
pad_msg_reader_ = node_->CreateReader<PadMessage>(
config_.topic_config().planning_pad_topic(),
[this](const std::shared_ptr<PadMessage>& pad_msg) {
ADEBUG << "Received pad data: run pad callback.";
std::lock_guard<std::mutex> lock(mutex_);
pad_msg_.CopyFrom(*pad_msg);
});
story_telling_reader_ = node_->CreateReader<Stories>(
config_.topic_config().story_telling_topic(),
[this](const std::shared_ptr<Stories>& stories) {
ADEBUG << "Received story_telling data: run story_telling callback.";
std::lock_guard<std::mutex> lock(mutex_);
stories_.CopyFrom(*stories);
});
if (FLAGS_use_navigation_mode) {
relative_map_reader_ = node_->CreateReader<MapMsg>(
config_.topic_config().relative_map_topic(),
[this](const std::shared_ptr<MapMsg>& map_message) {
ADEBUG << "Received relative map data: run relative map callback.";
std::lock_guard<std::mutex> lock(mutex_);
relative_map_.CopyFrom(*map_message);
});
}
planning_writer_ = node_->CreateWriter<ADCTrajectory>(
config_.topic_config().planning_trajectory_topic());
rerouting_writer_ = node_->CreateWriter<RoutingRequest>(
config_.topic_config().routing_request_topic());
planning_learning_data_writer_ = node_->CreateWriter<PlanningLearningData>(
config_.topic_config().planning_learning_data_topic());
return true;
}
bool PlanningComponent::Proc(
const std::shared_ptr<prediction::PredictionObstacles>&
prediction_obstacles,
const std::shared_ptr<canbus::Chassis>& chassis,
const std::shared_ptr<localization::LocalizationEstimate>&
localization_estimate) {
ACHECK(prediction_obstacles != nullptr);
// check and process possible rerouting request
CheckRerouting();
// process fused input data
local_view_.prediction_obstacles = prediction_obstacles;
local_view_.chassis = chassis;
local_view_.localization_estimate = localization_estimate;
{
std::lock_guard<std::mutex> lock(mutex_);
if (!local_view_.routing ||
hdmap::PncMap::IsNewRouting(*local_view_.routing, routing_)) {
local_view_.routing =
std::make_shared<routing::RoutingResponse>(routing_);
}
}
{
std::lock_guard<std::mutex> lock(mutex_);
local_view_.traffic_light =
std::make_shared<TrafficLightDetection>(traffic_light_);
local_view_.relative_map = std::make_shared<MapMsg>(relative_map_);
}
{
std::lock_guard<std::mutex> lock(mutex_);
local_view_.pad_msg = std::make_shared<PadMessage>(pad_msg_);
}
{
std::lock_guard<std::mutex> lock(mutex_);
local_view_.stories = std::make_shared<Stories>(stories_);
}
if (!CheckInput()) {
AERROR << "Input check failed";
return false;
}
if (config_.learning_mode() != PlanningConfig::NO_LEARNING) {
// data process for online training
message_process_.OnChassis(*local_view_.chassis);
message_process_.OnPrediction(*local_view_.prediction_obstacles);
message_process_.OnRoutingResponse(*local_view_.routing);
message_process_.OnStoryTelling(*local_view_.stories);
message_process_.OnTrafficLightDetection(*local_view_.traffic_light);
message_process_.OnLocalization(*local_view_.localization_estimate);
}
// publish learning data frame for RL test
if (config_.learning_mode() == PlanningConfig::RL_TEST) {
PlanningLearningData planning_learning_data;
LearningDataFrame* learning_data_frame =
injector_->learning_based_data()->GetLatestLearningDataFrame();
if (learning_data_frame) {
planning_learning_data.mutable_learning_data_frame()
->CopyFrom(*learning_data_frame);
common::util::FillHeader(node_->Name(), &planning_learning_data);
planning_learning_data_writer_->Write(planning_learning_data);
} else {
AERROR << "fail to generate learning data frame";
return false;
}
return true;
}
ADCTrajectory adc_trajectory_pb;
planning_base_->RunOnce(local_view_, &adc_trajectory_pb);
auto start_time = adc_trajectory_pb.header().timestamp_sec();
common::util::FillHeader(node_->Name(), &adc_trajectory_pb);
// modify trajectory relative time due to the timestamp change in header
const double dt = start_time - adc_trajectory_pb.header().timestamp_sec();
for (auto& p : *adc_trajectory_pb.mutable_trajectory_point()) {
p.set_relative_time(p.relative_time() + dt);
}
planning_writer_->Write(adc_trajectory_pb);
// record in history
auto* history = injector_->history();
history->Add(adc_trajectory_pb);
return true;
}
void PlanningComponent::CheckRerouting() {
auto* rerouting = injector_->planning_context()
->mutable_planning_status()
->mutable_rerouting();
if (!rerouting->need_rerouting()) {
return;
}
common::util::FillHeader(node_->Name(), rerouting->mutable_routing_request());
rerouting->set_need_rerouting(false);
rerouting_writer_->Write(rerouting->routing_request());
}
bool PlanningComponent::CheckInput() {
ADCTrajectory trajectory_pb;
auto* not_ready = trajectory_pb.mutable_decision()
->mutable_main_decision()
->mutable_not_ready();
if (local_view_.localization_estimate == nullptr) {
not_ready->set_reason("localization not ready");
} else if (local_view_.chassis == nullptr) {
not_ready->set_reason("chassis not ready");
} else if (HDMapUtil::BaseMapPtr() == nullptr) {
not_ready->set_reason("map not ready");
} else {
// nothing
}
if (FLAGS_use_navigation_mode) {
if (!local_view_.relative_map->has_header()) {
not_ready->set_reason("relative map not ready");
}
} else {
if (!local_view_.routing->has_header()) {
not_ready->set_reason("routing not ready");
}
}
if (not_ready->has_reason()) {
AERROR << not_ready->reason() << "; skip the planning cycle.";
common::util::FillHeader(node_->Name(), &trajectory_pb);
planning_writer_->Write(trajectory_pb);
return false;
}
return true;
}
} // namespace planning
} // namespace apollo
| 0
|
apollo_public_repos/apollo/modules
|
apollo_public_repos/apollo/modules/planning/planning.BUILD
|
load("@rules_cc//cc:defs.bzl", "cc_library")
cc_library(
name = "planning",
includes = ["include"],
hdrs = glob(["include/**/*.h"]),
srcs = glob(["lib/**/*.so*"]),
include_prefix = "modules/planning",
strip_include_prefix = "include",
visibility = ["//visibility:public"],
)
| 0
|
apollo_public_repos/apollo/modules/planning
|
apollo_public_repos/apollo/modules/planning/testdata/garage.csv
|
x,y,z,speed,acceleration,curvature,curvature_change_rate,time,theta,gear,s,throttle,brake,steering
586385.858607, 4140674.7357, -28.3670201628, 0.216666668653, 0.887545286694, 0.0227670812611, -0.0177396744278, 1496957374.6140, 2.83470068837, 1, 0.00216666668653, 22.0157165527, 13.6934461594, 12.6382980347
586385.855147, 4140674.73686, -28.3671755996, 0.216666668653, 0.913474615633, 0.0227670812611, 0.0, 1496957374.6246, 2.83481834381, 1, 0.00433333337307, 22.0157165527, 13.6751356125, 12.6382980347
586385.851608, 4140674.73803, -28.367333333, 0.252777785063, 0.884692224513, 0.0226902109692, -0.0304102244818, 1496957374.6342, 2.83493944838, 1, 0.0068611112237, 22.1026935577, 13.6751356125, 12.5957450867
586385.847987, 4140674.73924, -28.3675015001, 0.252777785063, 0.874161013299, 0.0226902109692, 0.0, 1496957374.6438, 2.83501097239, 1, 0.00938888907433, 22.1026935577, 13.7239646912, 12.5957450867
586385.84427, 4140674.74047, -28.3676676499, 0.283333331347, 0.934226919562, 0.0226517749143, -0.0135656665111, 1496957374.6543, 2.83511769878, 1, 0.0122222223878, 22.1026935577, 13.7239646912, 12.574467659
586385.840443, 4140674.74175, -28.3678200571, 0.283333331347, 1.03466084553, 0.0226517749143, 0.0, 1496957374.6639, 2.83524237155, 1, 0.0150555557013, 22.1026935577, 13.6507205963, 12.574467659
586385.836527, 4140674.74305, -28.3679780131, 0.31111112237, 1.02275571276, 0.0225749078732, -0.0247072623403, 1496957374.6745, 2.83535456498, 1, 0.018166666925, 22.114900589, 13.6507205963, 12.531914711
586385.832523, 4140674.74437, -28.3681540545, 0.31111112237, 0.965700419625, 0.0225749078732, 0.0, 1496957374.6841, 2.83546712465, 1, 0.0212777781487, 22.114900589, 13.6537723541, 12.531914711
586385.828455, 4140674.74571, -28.368321253, 0.338888883591, 0.836593771705, 0.0224980429898, -0.0226814413375, 1496957374.6936, 2.83562021513, 1, 0.0246666669846, 22.163728714, 13.6537723541, 12.489361763
586385.824334, 4140674.74708, -28.3684622813, 0.338888883591, 0.697852282292, 0.0224980429898, 0.0, 1496957374.7041, 2.8357196816, 1, 0.0280555558205, 22.163728714, 13.6751356125, 12.489361763
586385.820131, 4140674.74848, -28.3685834166, 0.363888889551, 0.722275690291, 0.0223827496946, -0.0316836535974, 1496957374.7146, 2.83585535814, 1, 0.031694444716, 22.2613868713, 13.6751356125, 12.425532341
586385.81583, 4140674.7499, -28.3687009905, 0.363888889551, 0.858753827361, 0.0223827496946, 0.0, 1496957374.7242, 2.83597623605, 1, 0.0353333336115, 22.2613868713, 13.6842908859, 12.425532341
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| 0
|
apollo_public_repos/apollo/modules/planning
|
apollo_public_repos/apollo/modules/planning/testdata/garage_error.csv
|
x,y,z,speed,acceleration,curvature,curvature_change_rate,time,theta,gear,s,throttle,brake,steering
586385.858607, 4140674.7357, -28.3670201628, 0.216666668653, 0.887545286694, 0.0227670812611, -0.0177396744278, 1496957374.6140, 2.83470068837, 1, 0.00216666668653, 22.0157165527, 13.6934461594, 12.6382980347
0.0, 1496957374.6246, 2.83481834381, 1, 0.00433333337307, 22.0157165527, 13.6751356125, 12.6382980347
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/out_of_map_prediction.pb.txt
|
header {
timestamp_sec: 1502920656.19
module_name: "prediction"
sequence_num: 5977
}
perception_error_code: OK
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/result_out_of_map_0.pb.txt
|
header {
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camera_timestamp: 0
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status {
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msg: "Failed to create reference line"
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}
gear: GEAR_DRIVE
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decision {
main_decision {
not_ready {
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}
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routing_header {
timestamp_sec: 1234.5
module_name: "routing"
sequence_num: 1
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/1_chassis.pb.txt
|
engine_started: true
engine_rpm: 1137.5
speed_mps: 0.0
odometer_m: 0.0
fuel_range_m: 0
throttle_percentage: 15.0438699722
brake_percentage: 17.9583435059
steering_percentage: -0.617021262646
steering_torque_nm: 0.0
parking_brake: false
driving_mode: EMERGENCY_MODE
error_code: NO_ERROR
gear_location: GEAR_REVERSE
header {
timestamp_sec: 1504387654.53
module_name: "chassis"
sequence_num: 69777
}
signal {
turn_signal: TURN_NONE
horn: false
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/result_planning_componnet_stop_obstacle_0.pb.txt
|
header {
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/stop_obstacle_chassis.pb.txt
|
engine_started: true
engine_rpm: 0.0
speed_mps: 4.26111125946
odometer_m: 0.0
fuel_range_m: 0
throttle_percentage: 25.1132984161
brake_percentage: 13.4996566772
steering_percentage: -40.872341156
steering_torque_nm: -0.375
parking_brake: false
driving_mode: COMPLETE_AUTO_DRIVE
error_code: NO_ERROR
gear_location: GEAR_DRIVE
header {
timestamp_sec: 1498682816.13
module_name: "chassis"
sequence_num: 170682
}
signal {
turn_signal: TURN_NONE
horn: false
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/follow_localization.pb.txt
|
header {
timestamp_sec: 1498682818.12
module_name: "localization"
sequence_num: 170449
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| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/garage_localization.pb.txt
|
header {
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| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/garage_prediction.pb.txt
|
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a: 2.20234333945e-05
relative_time: 2.5
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trajectory_point {
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v: 8.00000883109
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relative_time: 2.6
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trajectory_point {
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trajectory_point {
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perception_error_code: OK
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/stop_dest_chassis.pb.txt
|
engine_started: true
engine_rpm: 0.0
speed_mps: 4.42500019073
odometer_m: 0.0
fuel_range_m: 0
throttle_percentage: 15.2880144119
brake_percentage: 18.4710464478
steering_percentage: 3.34042549133
steering_torque_nm: -0.125
parking_brake: false
driving_mode: COMPLETE_AUTO_DRIVE
error_code: NO_ERROR
gear_location: GEAR_DRIVE
header {
timestamp_sec: 1502920656.46
module_name: "chassis"
sequence_num: 98066
}
signal {
turn_signal: TURN_NONE
horn: false
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/garage_routing.pb.txt
|
header {
module_name: "routing"
timestamp_sec: 1234.5
sequence_num: 1
}
routing_request {
waypoint {
id: "1_-1"
s: 0.0
pose {
x: 586392.840030
y: 4140673.012320
}
}
waypoint {
id: "1_-1"
s: 153.0
pose {
x: 586367.706490
y: 4140785.357946
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}
}
road {
passage {
can_exit: true
segment {
id: "1_-1"
start_s: 0.0
end_s: 153.0
}
}
}
measurement {
distance: 153.0
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/stop_obstacle_localization.pb.txt
|
header {
timestamp_sec: 1498682816.13
module_name: "localization"
sequence_num: 170250
}
pose {
position {
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y: 4140690.05199
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orientation {
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qw: -0.998679329034
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linear_velocity {
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linear_acceleration {
x: 1.03984377863
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z: -0.163916348384
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angular_velocity {
x: 0.00449323331444
y: 0.0405418149058
z: -0.346677548288
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heading: 1.66027769535
linear_acceleration_vrf {
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angular_velocity_vrf {
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y: 0.0554569487516
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}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/stop_obstacle_prediction.pb.txt
|
header {
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sequence_num: 987
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trajectory_point {
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trajectory_point {
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trajectory_point {
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trajectory_point {
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perception_error_code: OK
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/garage_chassis.pb.txt
|
engine_started: true
engine_rpm: 0.0
speed_mps: 0.0
odometer_m: 0.0
fuel_range_m: 0
throttle_percentage: 15.2391853333
brake_percentage: 13.6079959869
steering_percentage: 5.65957450867
steering_torque_nm: -0.3125
parking_brake: false
driving_mode: COMPLETE_MANUAL
error_code: NO_ERROR
gear_location: GEAR_NEUTRAL
header {
timestamp_sec: 1498682801.33
module_name: "chassis"
sequence_num: 169202
}
signal {
turn_signal: TURN_NONE
horn: false
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/1_prediction.pb.txt
|
header {
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module_name: "prediction"
sequence_num: 6968
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perception_error_code: OK
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/follow_prediction.pb.txt
|
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theta: 1.30472444734
}
v: 8.00001543812
a: 2.20234333945e-05
relative_time: 2.9
}
}
}
perception_error_code: OK
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/out_of_map_localization.pb.txt
|
header {
timestamp_sec: 1502920656.46
module_name: "localization"
sequence_num: 98168
}
pose {
position {
x: 586368.0
y: 4140790.0
z: -29.4437792711
}
orientation {
qx: -0.0183705362837
qy: -0.0228083896321
qz: -0.141161582559
qw: 0.989553287281
}
linear_velocity {
x: 1.27483825735
y: 4.30410215192
z: -0.0719737933875
}
linear_acceleration {
x: -0.305338168846
y: 0.0185947050156
z: 0.302948333827
}
angular_velocity {
x: 0.0197592682212
y: 0.00492437047244
z: 0.0328439277022
}
heading: 1.28665083367
linear_acceleration_vrf {
x: -0.282784695629
y: -0.0767818497207
z: 0.315423868546
}
angular_velocity_vrf {
x: 0.0192325517336
y: 0.00927895368132
z: 0.0322088755546
}
euler_angles {
x: -0.0503704973808
y: 0.0299223773453
z: 1.28665083367
}
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/out_of_map_chassis.pb.txt
|
engine_started: true
engine_rpm: 0.0
speed_mps: 4.42500019073
odometer_m: 0.0
fuel_range_m: 0
throttle_percentage: 15.2880144119
brake_percentage: 18.4710464478
steering_percentage: 3.34042549133
steering_torque_nm: -0.125
parking_brake: false
driving_mode: COMPLETE_AUTO_DRIVE
error_code: NO_ERROR
gear_location: GEAR_DRIVE
header {
timestamp_sec: 1502920656.46
module_name: "chassis"
sequence_num: 98066
}
signal {
turn_signal: TURN_NONE
horn: false
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/follow_chassis.pb.txt
|
engine_started: true
engine_rpm: 0.0
speed_mps: 5.59999990463
odometer_m: 0.0
fuel_range_m: 0
throttle_percentage: 19.7299156189
brake_percentage: 13.443198204
steering_percentage: -9.68085098267
steering_torque_nm: -0.125
parking_brake: false
driving_mode: COMPLETE_AUTO_DRIVE
error_code: NO_ERROR
gear_location: GEAR_DRIVE
header {
timestamp_sec: 1498682818.12
module_name: "chassis"
sequence_num: 170881
}
signal {
turn_signal: TURN_NONE
horn: false
}
| 0
|
apollo_public_repos/apollo/modules/planning/testdata
|
apollo_public_repos/apollo/modules/planning/testdata/garage_test/1_localization.pb.txt
|
header {
timestamp_sec: 1504387654.54
module_name: "localization"
sequence_num: 76261
}
pose {
position {
x: 586354.030596
y: 4140735.52422
z: -31.6059667105
}
orientation {
qx: -0.0404090426784
qy: 0.0209871273231
qz: -0.129521941468
qw: 0.990530522718
}
linear_velocity {
x: 0.00782728700811
y: -0.00918280190205
z: -0.0039800614284
}
linear_acceleration {
x: 0.0247735825145
y: -0.0757700573061
z: 0.0952269470726
}
angular_velocity {
x: -0.000504004623404
y: -0.00115693066804
z: 0.000281194530964
}
heading: 1.3120887936
linear_acceleration_vrf {
x: 0.0405285594814
y: -0.0748066177448
z: 0.0904677248055
}
angular_velocity_vrf {
x: -0.000196577873601
y: -0.00126684246843
z: 0.000167472072548
}
euler_angles {
x: 0.0312284467472
y: 0.085593843457
z: 1.3120887936
}
}
| 0
|
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