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recording. + +Usage: + python 01_lane_changes.py + +Example: + python 01_lane_changes.py ../Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d +""" +import sys +import os +from openautomatumdronedata.dataset import droneDataset + + +def analyze_lane_changes(dataset_path): + print(f"Loading dataset from: {dataset_path}") + dataset = droneDataset(dataset_path) + dynWorld = dataset.dynWorld + + print(f"Vehicles found: {len(dynWorld)}") + + lane_change_counts = [] + + for dynObj in dynWorld.dynamicObjects.values(): + lane_ids = dynObj.lane_id_vec + if len(lane_ids) == 0: + continue + + changes = 0 + current_lane = lane_ids[0] + for lane in lane_ids[1:]: + if lane != current_lane: + changes += 1 + current_lane = lane + + lane_change_counts.append({ + "uuid": dynObj.UUID, + "type": dynObj.type, + "changes": changes, + }) + + sorted_by_changes = sorted(lane_change_counts, key=lambda x: x["changes"], reverse=True) + + print("\n--- Top 10 vehicles with most lane changes ---") + for idx, item in enumerate(sorted_by_changes[:10]): + print(f"{idx+1}. Vehicle {item['uuid']} ({item['type']}): {item['changes']} lane changes") + + +if __name__ == "__main__": + if len(sys.argv) < 2: + print("Usage: python 01_lane_changes.py ") + else: + analyze_lane_changes(sys.argv[1]) diff --git a/example_scripts/02_heatmap_density.py b/example_scripts/02_heatmap_density.py new file mode 100644 index 0000000000000000000000000000000000000000..f8478847060cb95ceab00cb293538219f86f230a --- /dev/null +++ b/example_scripts/02_heatmap_density.py @@ -0,0 +1,58 @@ +""" +Traffic Density Heatmap — Automatum Data Roundabout Dataset +Generates a 2D heatmap of all vehicle positions over time. + +Usage: + python 02_heatmap_density.py + +Example: + python 02_heatmap_density.py ../Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d + +Output: + traffic_heatmap.png in the current directory +""" +import sys +import os +import numpy as np +import matplotlib.pyplot as plt +from openautomatumdronedata.dataset import droneDataset + + +def generate_density_heatmap(dataset_path, output_filename="traffic_heatmap.png"): + print(f"Loading dataset from: {dataset_path}") + dataset = droneDataset(dataset_path) + dynWorld = dataset.dynWorld + + print("Extracting position data...") + all_x, all_y = [], [] + + for dynObj in dynWorld.dynamicObjects.values(): + x_valid = [x for x in dynObj.x_vec if not np.isnan(x)] + y_valid = [y for y in dynObj.y_vec if not np.isnan(y)] + all_x.extend(x_valid) + all_y.extend(y_valid) + + if not all_x: + print("No position data found!") + return + + print(f"Extracted {len(all_x)} data points. Creating heatmap...") + + plt.figure(figsize=(10, 10)) + plt.style.use("dark_background") + plt.hist2d(all_x, all_y, bins=(200, 200), cmap="inferno", cmin=1) + plt.colorbar(label="Traffic density (data points)") + plt.title("Roundabout Traffic Density Heatmap (Top-View)") + plt.xlabel("X-Position [m]") + plt.ylabel("Y-Position [m]") + plt.gca().set_aspect("equal", adjustable="box") + plt.tight_layout() + plt.savefig(output_filename, dpi=300) + print(f"Heatmap saved: {os.path.abspath(output_filename)}") + + +if __name__ == "__main__": + if len(sys.argv) < 2: + print("Usage: python 02_heatmap_density.py ") + else: + generate_density_heatmap(sys.argv[1]) diff --git a/example_scripts/03_high_acceleration.py b/example_scripts/03_high_acceleration.py new file mode 100644 index 0000000000000000000000000000000000000000..114d5de72be515dfe05306ecd825d2da2d7f241e --- /dev/null +++ b/example_scripts/03_high_acceleration.py @@ -0,0 +1,61 @@ +""" +High Acceleration Detection — Automatum Data Roundabout Dataset +Detects vehicles exceeding a given acceleration threshold. + +Usage: + python 03_high_acceleration.py [threshold_m_s2] + +Example: + python 03_high_acceleration.py ../Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d 3.0 +""" +import sys +import os +import numpy as np +from openautomatumdronedata.dataset import droneDataset + + +def detect_high_accelerations(dataset_path, acc_threshold=3.0): + print(f"Loading dataset from: {dataset_path}") + dataset = droneDataset(dataset_path) + dynWorld = dataset.dynWorld + + print(f"Searching for accelerations > {acc_threshold} m/s^2...") + + high_accel_vehicles = [] + + for dynObj in dynWorld.dynamicObjects.values(): + length = min(len(dynObj.ax_vec), len(dynObj.ay_vec)) + if length == 0: + continue + + ax = np.array(dynObj.ax_vec[:length]) + ay = np.array(dynObj.ay_vec[:length]) + total_accel = np.sqrt(ax**2 + ay**2) + valid_accel = total_accel[~np.isnan(total_accel)] + + if len(valid_accel) > 0: + max_accel = np.max(valid_accel) + if max_accel > acc_threshold: + high_accel_vehicles.append({ + "uuid": dynObj.UUID, + "type": dynObj.type, + "max_accel": max_accel, + }) + + if not high_accel_vehicles: + print(f"No vehicles with acceleration > {acc_threshold} m/s^2 found.") + return + + sorted_vehicles = sorted(high_accel_vehicles, key=lambda x: x["max_accel"], reverse=True) + + print(f"\n--- {len(sorted_vehicles)} vehicles with notable acceleration ---") + for item in sorted_vehicles: + print(f"Vehicle {item['uuid']} ({item['type']}): max {item['max_accel']:.2f} m/s^2") + + +if __name__ == "__main__": + if len(sys.argv) < 2: + print("Usage: python 03_high_acceleration.py [threshold]") + else: + threshold = float(sys.argv[2]) if len(sys.argv) >= 3 else 3.0 + detect_high_accelerations(sys.argv[1], threshold) diff --git a/example_scripts/README.md b/example_scripts/README.md new file mode 100644 index 0000000000000000000000000000000000000000..76f6b56d801234d10d39086489cd67cd55265d98 --- /dev/null +++ b/example_scripts/README.md @@ -0,0 +1,32 @@ +# Example Scripts — Automatum Data Roundabout Dataset + +These scripts demonstrate how to work with the Automatum drone traffic data using the `openautomatumdronedata` Python library. + +## Prerequisites + +```bash +pip install openautomatumdronedata numpy matplotlib +``` + +## Scripts + +| Script | Description | +|--------|-------------| +| `01_lane_changes.py` | Analyzes lane change frequency per vehicle and shows the top 10 | +| `02_heatmap_density.py` | Creates a traffic density heatmap from all position data | +| `03_high_acceleration.py` | Detects vehicles exceeding an acceleration threshold | + +## Usage + +All scripts take the path to a recording folder as their first argument: + +```bash +python 01_lane_changes.py ../Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d +python 02_heatmap_density.py ../Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d +python 03_high_acceleration.py ../Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d 3.0 +``` + +## Learn More + +- [Full Documentation](https://openautomatumdronedata.readthedocs.io) +- [Automatum Data Website](https://automatum-data.com) diff --git a/website_information/.DS_Store b/website_information/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..7d56b052244e0778a3452abd6a3878545e334857 Binary files /dev/null and b/website_information/.DS_Store differ diff --git a/website_information/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d_map.jpg b/website_information/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d_map.jpg new file mode 100644 index 0000000000000000000000000000000000000000..8e570ff03c1da8367f77054ea0d2a7e7bdeed3e4 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form must reproduce the above copyright notice, +this list of conditions and the following disclaimer in the documentation +and/or other materials provided with the distribution. + +Neither the name of Anaconda nor the names of any contributors +may be used to endorse or promote products derived from this software +without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF +THE POSSIBILITY OF SUCH DAMAGE. \ No newline at end of file diff --git a/website_information/img/Illustration-3.jpg b/website_information/img/Illustration-3.jpg new file mode 100644 index 0000000000000000000000000000000000000000..746a1c8878e3c37b49cdde2fcc555ce1c0bde3cf --- /dev/null +++ b/website_information/img/Illustration-3.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0b9287acfe10df4dfaa33c3a1fc579acacca950477da2b18e397ad7363f91bf4 +size 2760658 diff --git "a/website_information/img/automatum_logo_waagerecht_gro\303\237.png" "b/website_information/img/automatum_logo_waagerecht_gro\303\237.png" new file mode 100644 index 0000000000000000000000000000000000000000..1610c293a8144d88884a8125f47199c78f0e8466 --- /dev/null +++ "b/website_information/img/automatum_logo_waagerecht_gro\303\237.png" @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eded7ce43163ecb898166a7bc587235f59b15bd17856235867d404760ca54c3e +size 42970 diff --git a/website_information/img/icon_automatumd_data_roundaboud.jpg b/website_information/img/icon_automatumd_data_roundaboud.jpg new file mode 100644 index 0000000000000000000000000000000000000000..2e0b2c217569db11d67d2d48f7e1c7e6f82d78ad --- /dev/null +++ b/website_information/img/icon_automatumd_data_roundaboud.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:345730127d848523e85e4dbb513a5386309a648c0ee1eb23398cc6ed4a875ccd +size 3432723 diff --git a/website_information/website_licence_information.json b/website_information/website_licence_information.json new file mode 100644 index 0000000000000000000000000000000000000000..a2b4373b30af9898db9f96ecc9e479c46f0e3b9e --- /dev/null +++ b/website_information/website_licence_information.json @@ -0,0 +1 @@ +{"number_of_hours": 0.11726541356170986, "number_of_kilometers": 26.003707263676624, "number_of_recordings": 2, "number_of_locations": 2, "date": "27.03.2023, 12:52:29", "version": "26bfa8c6-831b-4e31-a81e-48be9fe0123c", "max_length_trajectory": 125.5127824099631, "object_deviation": [{"title": "Car", "value": 207, "color": "#763626"}, {"title": "Truck", "value": 3, "color": "#336B87"}, {"title": "Van", "value": 2, "color": "#2A3132"}], "locations": {"Koesching": {"name": "Koesching", "number_of_recordings": 1, "number_of_hours": 0.03708337967597227, "number_of_kilometers": 8.032818074237637, "lat": 48.808699999999995, "long": 11.4804, "max_length_trajectory": 125.5127824099631, "number_of_objects": 64, "path_slider_img_one": "website_licence_information/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d/sliding_img_base_cropped.jpg", "path_slider_img_two": "website_licence_information/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d/sliding_img_whie_overlay_cropped.jpg", "path_map_png": "website_licence_information/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d/Roundabout-KoeschingerTor-Koesching_19bb-19bbabb9-6c81-4a15-af8c-50fc251a248d_map.jpg"}, "IngolstadtVOC": {"name": "IngolstadtVOC", "number_of_recordings": 1, "number_of_hours": 0.08018203388573758, "number_of_kilometers": 17.97088918943899, "lat": 48.784099999999995, "long": 11.4821, "max_length_trajectory": 121.42492695566884, "number_of_objects": 148, "path_slider_img_one": "website_licence_information/Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d/sliding_img_base_cropped.jpg", "path_slider_img_two": "website_licence_information/Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d/sliding_img_whie_overlay_cropped.jpg", "path_map_png": "website_licence_information/Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d/Roundabout-St2231-IngolstadtVOC_e63d-e63db143-1e40-4945-8866-464572ebf75d_map.jpg"}}} \ No newline at end of file