KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients

Project Page | Paper | Supplementary

This repository contains the code for the ECCV 2022 paper KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients. If you find this repository useful, please cite

@inproceedings{Hanselmann2022ECCV,
  author = {Hanselmann, Niklas and Renz, Katrin and Chitta, Kashyap and Bhattacharyya, Apratim and Geiger, Andreas},
  title = {KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients},
  booktitle = {European Conference on Computer Vision(ECCV)},
  year = {2022}
}

Setup
Scenario Generation
Fine-tuning
Town10 Intersections
Acknowledgements

Setup

Install anaconda

wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
bash Anaconda3-2022.05-Linux-x86_64.sh
source ~/.profile

Clone the repo and build the environment

git clone https://github.com/autonomousvision/king
cd king
conda env create -f environment.yml
conda activate king

Download and setup CARLA 0.9.10.1

chmod +x setup_carla.sh
./setup_carla.sh

Running the code

We provide bash scripts for the experiments for convenience. Please make sure the "CARLA_ROOT" ("./carla_server" by default) and "KING_ROOT" (if present) environment variables are set correctly in all of those scripts.

KING Scenario Generation

For all of the generation scripts, first spin up a carla server in a separate shell:

carla_server/CarlaUE4.sh --world-port=2000 -opengl

Then run the following script for AIM-BEV generation:

bash run_generation.sh

This script runs generation for all traffic density and automatically evaluates the results. For AIM-BEV generation using both gradient paths, run:

bash run_generation_both_paths.sh

Finally, to generate scenarios for TransFuser, first download the model weights:

mkdir driving_agents/king/transfuser/model_checkpoints/regular
cd driving_agents/king/transfuser/model_checkpoints/regular
wget https://s3.eu-central-1.amazonaws.com/avg-projects/transfuser/models.zip
unzip models.zip
rm -rf models.zip late_fusion geometric_fusion cilrs aim

Then change back to root directory of the repository and run:

bash run_generation_transfuser.sh

Fine-tuning

To fine-tune the original agent on KING scenarios, first download the regular data for AIM-BEV:

chmod +x download_regular_data.sh
./download_regular_data.sh

Then run the fine-tuning script (and adjust it for the correct dataset path, if necessary):

bash run_fine_tuning.sh

This script also automatically runs evaluation on KING scenarios.

Town10 Intersections

To evaluate the original checkpoint for AIM-BEV on the Town10 intersections benchmark, spin up a carla server and run

leaderboard/scripts/run_evaluation.sh

To evaluate a fine-tuned model, run the fine-tuning script above and toggle the commented "TEAM_CONFIG" variable in the evaluation script to change the model weights.

Acknowledgements

This implementation is based on code from several repositories. We sincerely thank the authors for their awesome work.

Also, check out the code for other recent work on CARLA from our group:

mariammaher550/king