https://github.com/autonomousvision/navsim
[NeurIPS 2024] NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
https://github.com/autonomousvision/navsim
autonomous-driving planning self-driving
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[NeurIPS 2024] NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
- Host: GitHub
- URL: https://github.com/autonomousvision/navsim
- Owner: autonomousvision
- License: apache-2.0
- Created: 2024-01-20T09:42:31.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-24T21:10:29.000Z (6 months ago)
- Last Synced: 2025-04-24T22:28:59.163Z (6 months ago)
- Topics: autonomous-driving, planning, self-driving
- Language: Python
- Homepage:
- Size: 33.8 MB
- Stars: 473
- Watchers: 15
- Forks: 41
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- Awesome-LLM4AD - NAVSIM
README
Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
Paper | Supplementary | Talk | 2024 Challenge | Leaderboard v1.1 | Warmup Leaderboard v2.0
> [**NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking**](https://arxiv.org/abs/2406.15349)
>
> [Daniel Dauner](https://danieldauner.github.io/)1,2, [Marcel Hallgarten](https://mh0797.github.io/)1,5, [Tianyu Li](https://github.com/sephyli)3, [Xinshuo Weng](https://xinshuoweng.com/)4, [Zhiyu Huang](https://mczhi.github.io/)4,6, [Zetong Yang](https://scholar.google.com/citations?user=oPiZSVYAAAAJ)3\
> [Hongyang Li](https://lihongyang.info/)3, [Igor Gilitschenski](https://www.gilitschenski.org/igor/)7,8, [Boris Ivanovic](https://www.borisivanovic.com/)4, [Marco Pavone](https://web.stanford.edu/~pavone/)4,9, [Andreas Geiger](https://www.cvlibs.net/)1,2, and [Kashyap Chitta](https://kashyap7x.github.io/)1,2
>
> 1University of Tübingen, 2Tübingen AI Center, 3OpenDriveLab at Shanghai AI Lab, 4NVIDIA Research\
> 5Robert Bosch GmbH, 6Nanyang Technological University, 7University of Toronto, 8Vector Institute, 9Stanford University
>
> Advances in Neural Information Processing Systems (NeurIPS), 2024 \
> Track on Datasets and Benchmarks
🔥 NAVSIM gathers simulation-based metrics (such as progress and time to collision) for end-to-end driving by unrolling simplified bird's eye view abstractions of scenes for a short simulation horizon. It operates under the condition that the policy has limited influence on the environment, which enables **efficient, open-loop metric computation** while being **better aligned with closed-loop** evaluations than traditional displacement errors.
## Table of Contents
1. [Highlights](#highlight)
2. [Getting started](#gettingstarted)
3. [Changelog](#changelog)
4. [License and citation](#licenseandcitation)
5. [Other resources](#otherresources)
- [Download and installation](docs/install.md)
- [Understanding and creating agents](docs/agents.md)
- [Understanding the data format and classes](docs/cache.md)
- [Dataset splits vs. filtered training / test splits](docs/splits.md)
- [Understanding the Extended PDM Score](docs/metrics.md)
- [Understanding the traffic simulation](docs/traffic_agents.md)
- [Submitting to the Leaderboard](docs/submission.md)
## Changelog
- **`[2025/02/28]`** NAVSIM v2.0 release (official devkit version for 2025 warm-up phase)
- Extends the PDM Score with more metrics and penalties (see [metrics](docs/metrics.md))
- Adds a new two-stage pseudo closed-loop simulation (see [metrics](docs/metrics.md))
- Adds support for reactive traffic agent policies (see [traffic simulation](docs/metrics.md))
- **`[2024/09/03]`** NAVSIM v1.1 release
- Leaderboard for `navtest` on [Hugging Face](https://huggingface.co/spaces/AGC2024-P/e2e-driving-navsim)
- Release of baseline checkpoints on [Hugging Face](https://huggingface.co/autonomousvision/navsim_baselines)
- Updated docs for [submission](docs/submission.md) and [paper](https://arxiv.org/abs/2406.15349)
- Code refactoring, formatting, minor fixes
- **`[2024/04/21]`** NAVSIM v1.0 release (official devkit version for [AGC 2024](https://opendrivelab.com/challenge2024/#end_to_end_driving_at_scale))
- Parallelization of metric caching / evaluation
- Adds [Transfuser](https://arxiv.org/abs/2205.15997) baseline (see [agents](docs/agents.md#Baselines))
- Adds standardized training and test filtered splits (see [splits](docs/splits.md))
- Visualization tools (see [tutorial_visualization.ipynb](tutorial/tutorial_visualization.ipynb))
- **`[2024/04/03]`** NAVSIM v0.4 release
- Support for test phase frames of competition
- Download script for trainval
- Egostatus MLP Agent and training pipeline
- **`[2024/03/25]`** NAVSIM v0.3 release (official devkit version for warm-up phase)
- Adds code for Leaderboard submission
- **`[2024/03/11]`** NAVSIM v0.2 release
- Easier installation and download
- mini and test data split integration
- Privileged `Human` agent
- **`[2024/02/20]`** NAVSIM v0.1 release (initial demo)
- OpenScene-mini sensor blobs and annotation logs
- Naive `ConstantVelocity` agent
## License and citation
All assets and code in this repository are under the [Apache 2.0 license](./LICENSE) unless specified otherwise. The datasets (including nuPlan and OpenScene) inherit their own distribution licenses. Please consider citing our paper and project if they help your research.
```BibTeX
@inproceedings{Dauner2024NEURIPS,
author = {Daniel Dauner and Marcel Hallgarten and Tianyu Li and Xinshuo Weng and Zhiyu Huang and Zetong Yang and Hongyang Li and Igor Gilitschenski and Boris Ivanovic and Marco Pavone and Andreas Geiger and Kashyap Chitta},
title = {NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
year = {2024},
}
```
```BibTeX
@misc{Contributors2024navsim,
title={NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking},
author={NAVSIM Contributors},
howpublished={\url{https://github.com/autonomousvision/navsim}},
year={2024}
}
```
- [SLEDGE](https://github.com/autonomousvision/sledge) | [tuPlan garage](https://github.com/autonomousvision/tuplan_garage) | [CARLA garage](https://github.com/autonomousvision/carla_garage) | [Survey on E2EAD](https://github.com/OpenDriveLab/End-to-end-Autonomous-Driving)
- [PlanT](https://github.com/autonomousvision/plant) | [KING](https://github.com/autonomousvision/king) | [TransFuser](https://github.com/autonomousvision/transfuser) | [NEAT](https://github.com/autonomousvision/neat)