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Learning to drive from a world on rails
Dian Chen, Vladlen Koltun, Philipp Krähenbühl,
arXiv techical report (arXiv 2105.00636)

PWC

This repo contains code for our paper Learning to drive from a world on rails.

ProcGen code coming soon.

Reference

If you find our repo or paper useful, please cite us as

@inproceedings{chen2021learning,
  title={Learning to drive from a world on rails},
  author={Chen, Dian and Koltun, Vladlen and Kr{\"a}henb{\"u}hl, Philipp},
  booktitle={ICCV},
  year={2021}
}

Updates

Getting Started

Training

Evaluation

If you evaluating the pretrained weights, make sure you are launching CARLA with -vulkan!

Leaderboard routes

python evaluate.py --agent-config=[PATH TO CONFIG]

NoCrash routes

python evaluate_nocrash.py --town={Town01,Town02} --weather={train, test} --agent-config=[PATH TO CONFIG] --resume
python -m scripts.view_nocrash_results [PATH TO CONFIG.YAML]

Pretrained weights

Dataset

We also release the data we trained for the leaderboard. Checkout DATASET.md for more details.

Acknowledgements

The leaderboard codes are built from the original leaderboard repo. The scenariorunner codes are from the original scenario_runner repo. The waypointer.py GPS coordinate conversion codes are build from Marin Toromanoff's leadeboard submission.

License

This repo is released under the MIT License (please refer to the LICENSE file for details). The leaderboard repo which our leaderboard folder builds upon is under the MIT License.