README.md

---
license: apache-2.0
pretty_name: VehicleArena Road Networks
---

<h1 align="center">VehicleArena Road Networks</h1>

<p align="center"><strong>Offline map assets for VehicleArena's 3D urban-driving benchmark</strong></p>

<div align="center">
  <a href="https://github.com/OpenMOSS/VehicleArena"><img src="https://img.shields.io/badge/GitHub-Code-181717?logo=github&amp;logoColor=white" alt="VehicleArena code"></a>
  <a href="https://arxiv.org/abs/2609.35916"><img src="https://img.shields.io/badge/arXiv-2609.35916-B31B1B?logo=arxiv&amp;logoColor=white" alt="VehicleArena paper"></a>
  <a href="https://arxiv.org/pdf/2609.35916"><img src="https://img.shields.io/badge/PDF-Download-D32F2F?logo=adobeacrobatreader&amp;logoColor=white" alt="Download paper PDF"></a>
</div>

<p align="center"><a href="https://github.com/OpenMOSS/VehicleArena/blob/main/README.en.md">English project README</a> · <a href="https://github.com/OpenMOSS/VehicleArena/blob/main/README.md">中文项目说明</a></p>

This repository contains the versioned road-network bundle used by [VehicleArena](https://github.com/OpenMOSS/VehicleArena). The simulator, benchmark scenarios, evaluation code, and map installer live in the GitHub repository; the large offline maps are distributed here.

**Start here:** [Download](#-download) · [Install](#-installation) · [Benchmark context](#-benchmark-context) · [Citation](#-citation)

## 🌟 Highlights

- **116 road-network maps:** the archive contains 116 base road networks and their 116 lane-level counterparts, for 232 map JSON files in total.
- **Versioned and verifiable:** the archive follows CalVer `YYYY.MM.DD.PATCH`; the VehicleArena installer checks its SHA-256 and the individual map files against the code repository's manifest.
- **Maps, not trajectories:** task definitions and evaluation software are maintained on GitHub, so the same map bundle can be used with the published tasks or new scenarios.

## 📦 Download

| Item | Value |
| --- | --- |
| Version | `2026.09.22.0` |
| Archive | [vehiclearena-road-networks-2026.09.22.0.tar.gz](https://huggingface.co/datasets/OpenMOSS-Team/VehicleArena/resolve/main/vehiclearena-road-networks-2026.09.22.0.tar.gz?download=true) |
| Contents | 116 base + 116 lane-level networks (232 JSON files) |
| Size | 117,275,038 bytes |
| SHA-256 | `79e9b642db23c37373697b5431dd615846c57b7c9b7e2c520c64d4ed3d608f75` |

The archive can also be downloaded with the Hugging Face CLI:

```bash
hf download OpenMOSS-Team/VehicleArena \
  vehiclearena-road-networks-2026.09.22.0.tar.gz \
  --repo-type dataset --local-dir /path/to/downloads
```

## 🚀 Installation

First set up the [VehicleArena code and dependencies](https://github.com/OpenMOSS/VehicleArena#-quick-start). From the code repository root, install the downloaded archive and check the environment:

```bash
python scripts/manage_map_bundle.py install \
  --source /path/to/downloads/vehiclearena-road-networks-2026.09.22.0.tar.gz
python scripts/check_environment.py
```

The check reports `"ready": true` when Python, SUMO, and the maps are available. See the [map installation guide](https://github.com/OpenMOSS/VehicleArena/blob/main/vehiclearena/simulation/MAPS.md) for the archive layout and checksum validation.

## 📊 Benchmark context

The published VehicleArena benchmark has 100 training/development tasks and 112 held-out evaluation tasks: 80 Basic and 32 MultiLLM. Those tasks, their manifests, and the evaluation code are in [GitHub](https://github.com/OpenMOSS/VehicleArena), not in this map archive. The published time limits were calibrated using this map version; changing road data or task definitions requires recalibrating affected scenarios. Reusing the same archive with another evaluated model does not.

## 📎 Citation

If you use these maps with VehicleArena, please cite the [paper](https://arxiv.org/abs/2609.35916):

```bibtex
@article{yang2026vehiclearena,
  title={VehicleArena: A Realistic Urban Environment for Multi-Agent Driving},
  author={Yang, Jie and Chen, Jiajun and Zhou, Jiazheng and Huang, Mianqiu and Zheng, Yining and Wang, Yuxin and Qiu, Xipeng},
  journal={arXiv preprint arXiv:2609.35916},
  year={2026}
}
```