- Haochen Liu, Li Chen, Yu Qiao, Chen Lv and Hongyang Li
- Paper | Poster | Challenge Report
- If you have any questions, please feel free to contact: Haochen Liu ( [email protected] )
[2025-06] The ensembled version of BeTop BeTop-ens has received 3rd place of 2025 WOMD Interaction Prediction Challenge. Report
[2024-11] Scenario Token released for Test14-Inter. Link
[2024-11] Prediction project released.
BeTop leverages braid theory to model multi-agent future behaviors in autonomous driving;
The synergetic framework, BeTopNet, integrates topology reasoning with prediction and planning tasks for autonomous driving.
We provide the full prediction implementation of BeTopNet in Waymo Open Motion Dataset (WOMD).
Features:
- ✅ Full support for WOMD Prediction Challenges
- ✅ Flexible Toolbox for prediction tasks
- ✅ Pipeline for reproduced popular Baselines
- Initial release
- Prediction pipeline in WOMD
- Planning pipeline in nuPlan
If you find the project helpful for your research, please consider citing our paper:
@inproceedings{liu2024betop,
title={Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving},
author={Haochen Liu and Li Chen and Yu Qiao and Chen Lv and Hongyang Li},
booktitle={NeurIPS},
year={2024}
}