File size: 2,331 Bytes
7c4494a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | ---
task_categories:
- robotics
---
# Fail2Drive: Benchmarking Closed-Loop Driving Generalization
[**Project Page**](https://simonger.github.io/fail2drive/) | [**Paper**](https://huggingface.co/papers/2604.08535) | [**GitHub**](https://github.com/autonomousvision/fail2drive)
Fail2Drive is the first CARLA v2 benchmark designed to test closed-loop generalization on truly unseen long-tail scenarios. By pairing each shifted route with an in-distribution reference scenario, it exposes substantial hidden failure modes in current state-of-the-art driving models.
## Highlights
- **17 unseen scenarios** for evaluation of true generalization.
- **30 novel assets** including animals, visual noise, and adversarial obstacles.
- **Paired route design** enables quantification of the generalization gap.
- **100 route pairs** in diverse environments and configurations.
- **Toolbox** for creating custom obstacles and routes.
## Installation
To set up the environment and the Fail2Drive CARLA simulator, follow these steps:
```bash
# 1. Clone this repository
git clone https://github.com/autonomousvision/fail2drive.git
cd fail2drive
# 2. Set up the Fail2Drive CARLA simulator
mkdir f2d_carla
curl -L \
https://huggingface.co/datasets/SimonGer/fail2drive/resolve/main/fail2drive_simulator.tar.gz \
| tar -xz -C f2d_carla
# 3. Create the conda environment
conda env create -f environment.yml
conda activate fail2drive
# 4. Set environment variables
source env_vars.sh
```
## Sample Usage
To run a keyboard-controlled human agent on a benchmark route, start CARLA in a separate terminal and run:
```bash
python leaderboard/leaderboard/leaderboard_evaluator.py \
--agent ${WORK_DIR}/leaderboard/leaderboard/autoagents/human_agent_keyboard.py \
--routes ${WORK_DIR}/fail2drive_split/Generalization_PedestriansOnRoad_1085.xml
```
To run the PDM-Lite expert policy:
```bash
python leaderboard/leaderboard/leaderboard_evaluator_local.py \
--agent ${WORK_DIR}/team_code/visu_agent.py \
--track MAP \
--routes ${WORK_DIR}/fail2drive_split/Generalization_PedestriansOnRoad_1085.xml
```
## Citation
```bibtex
@article{gerstner2024fail2drive,
title={Fail2Drive: Benchmarking Closed-Loop Driving Generalization},
author={Gerstner, Simon and others},
journal={arXiv preprint arXiv:2604.08535},
year={2024}
}
``` |