# navsim

**Repository Path**: allingo/navsim

## Basic Information

- **Project Name**: navsim
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-04-29
- **Last Updated**: 2025-04-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<div id="top" align="center">

<p align="center">
  <img src="assets/navsim_transparent.png" width="600">
  <h2 align="center">Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking</h1>
  <h3 align="center"><a href="https://arxiv.org/abs/2406.15349">Paper</a> | <a href="https://danieldauner.github.io/assets/pdf/Dauner2024NIPS_supplementary.pdf">Supplementary</a> | <a href="https://www.youtube.com/watch?v=Qe76HRmPDe0">Talk</a> | <a href="https://opendrivelab.com/challenge2024/#end_to_end_driving_at_scale">2024 Challenge</a> | <a href="https://huggingface.co/spaces/AGC2025/e2e-driving-2025">Leaderboard v2</a> | <a href="https://huggingface.co/spaces/AGC2025/e2e-driving-warmup">Warmup Leaderboard v2</a> </h3>
</p>

</div>

<br/>

> [**NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking**](https://arxiv.org/abs/2406.15349)
>
> [Daniel Dauner](https://danieldauner.github.io/)<sup>1,2</sup>, [Marcel Hallgarten](https://mh0797.github.io/)<sup>1,5</sup>, [Tianyu Li](https://github.com/sephyli)<sup>3</sup>, [Xinshuo Weng](https://xinshuoweng.com/)<sup>4</sup>, [Zhiyu Huang](https://mczhi.github.io/)<sup>4,6</sup>, [Zetong Yang](https://scholar.google.com/citations?user=oPiZSVYAAAAJ)<sup>3</sup>\
> [Hongyang Li](https://lihongyang.info/)<sup>3</sup>, [Igor Gilitschenski](https://www.gilitschenski.org/igor/)<sup>7,8</sup>, [Boris Ivanovic](https://www.borisivanovic.com/)<sup>4</sup>, [Marco Pavone](https://web.stanford.edu/~pavone/)<sup>4,9</sup>, [Andreas Geiger](https://www.cvlibs.net/)<sup>1,2</sup>, and [Kashyap Chitta](https://kashyap7x.github.io/)<sup>1,2</sup>  <br>
>
> <sup>1</sup>University of Tübingen, <sup>2</sup>Tübingen AI Center, <sup>3</sup>OpenDriveLab at Shanghai AI Lab, <sup>4</sup>NVIDIA Research\
> <sup>5</sup>Robert Bosch GmbH, <sup>6</sup>Nanyang Technological University, <sup>7</sup>University of Toronto, <sup>8</sup>Vector Institute, <sup>9</sup>Stanford University
>
> Advances in Neural Information Processing Systems (NeurIPS), 2024 \
> Track on Datasets and Benchmarks
<br/>


## Highlights <a name="highlight"></a>

🔥 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.

This branch contains the code for NAVSIM v2, used in the 2025 NAVSIM challenge. For NAVSIM v1, as well as its `navtest` leaderboard, please check the [v1.1 branch](https://github.com/autonomousvision/navsim/tree/v1.1).

<p align="center">
  <img src="assets/navsim_cameras.gif" width="800">
</p>

## Table of Contents

1. [Highlights](#highlight)
2. [Getting started](#gettingstarted)
3. [Changelog](#changelog)
4. [License and citation](#licenseandcitation)
5. [Other resources](#otherresources)

## Getting started <a name="gettingstarted"></a>

- [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)

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## Changelog <a name="changelog"></a>
- **`[2025/04/28]`** NAVSIM v2.2 release (official devkit version for [AGC 2025](https://opendrivelab.com/challenge2025/#navsim-e2e-driving))
  - Release of `private_test_hard` dataset (see [splits](docs/splits.md)) for the [HuggingFace NAVSIM v2 End-to-End Driving Challenge 2025 Leaderboard](https://huggingface.co/spaces/AGC2025/e2e-driving-2025).
    - The submission deadline is 2025-05-11 00:00:00 UTC
    - You are limited to one upload per day on the challenge leaderboard, which should take approximately 2 hours to evaluate after a succesful submission.
  - Fixed bug in `openscene_meta_datas` for `navhard` and `warmup`
    - ⚠️ **IMPORTANT**: If you used `navhard_two_stage/openscene_meta_datas` or `warmup_two_stage/openscene_meta_datas` to evaluate your model, please re-download and use the new data.
- **`[2025/04/24]`** [NAVSIM v2.1.2](https://github.com/autonomousvision/navsim/tree/v2.1.2) release
  - Release of `navhard_two_stage` dataset (see [splits](docs/splits.md))
  - Updated Extended Predictive Driver Model Score (EPDMS) for the [Hugging Face Warmup leaderboard](https://huggingface.co/spaces/AGC2025/e2e-driving-warmup). See see [metrics](docs/metrics.md) for details regarding the implementation.
- **`[2025/04/13]`** [NAVSIM v2.1.1](https://github.com/autonomousvision/navsim/tree/v2.1.1) release
  - Updated dataset for the warmup leaderboard with minor fixes
- **`[2025/04/08]`** [NAVSIM v2.1](https://github.com/autonomousvision/navsim/tree/v2.1) release
  - Added new dataset for the [Hugging Face Warmup leaderboard](https://huggingface.co/spaces/AGC2025/e2e-driving-warmup) (see [submission](docs/submission.md))
  - Introduced support for two-stage reactive traffic agents (see [traffic simulation](docs/metrics.md))
- **`[2025/02/28]`** [NAVSIM v2.0](https://github.com/autonomousvision/navsim/tree/v2.0) release
  - 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](https://github.com/autonomousvision/navsim/tree/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)
- **`[2024/04/21]`** [NAVSIM v1.0](https://github.com/autonomousvision/navsim/tree/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](https://github.com/autonomousvision/navsim/tree/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](https://github.com/autonomousvision/navsim/tree/v0.3) release
  - Adds code for Leaderboard submission
- **`[2024/03/11]`** [NAVSIM v0.2](https://github.com/autonomousvision/navsim/tree/v0.2) release
  - Easier installation and download
  - mini and test data split integration
  - Privileged `Human` agent
- **`[2024/02/20]`** [NAVSIM v0.1](https://github.com/autonomousvision/navsim/tree/v0.1) release (initial demo)
  - OpenScene-mini sensor blobs and annotation logs
  - Naive `ConstantVelocity` agent

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## License and citation <a name="licenseandcitation"></a>

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}
}
```

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## Other resources <a name="otherresources"></a>

- [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)

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