The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge (2306.15914v1)
Abstract: In this technical report, we present the 2nd place solution of 2023 Waymo Open Sim Agents Challenge (WOSAC)[4]. We propose a simple yet effective autoregressive method for simulating multi-agent behaviors, which is built upon a well-known multimodal motion forecasting framework called Motion Transformer (MTR)[5] with postprocessing algorithms applied. Our submission named MTR+++ achieves 0.4697 on the Realism Meta metric in 2023 WOSAC. Besides, a modified model based on MTR named MTR_E is proposed after the challenge, which has a better score 0.4911 and is ranked the 3rd on the leaderboard of WOSAC as of June 25, 2023.
- Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction. arXiv preprint arXiv:1910.05449, 2019.
- Large scale interactive motion forecasting for autonomous driving : The waymo open motion dataset. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 9690–9699, 2021.
- Jfp: Joint future prediction with interactive multi-agent modeling for autonomous driving. In K. Liu, D. Kulic, and J. Ichnowski, editors, Proceedings of The 6th Conference on Robot Learning, volume 205 of Proceedings of Machine Learning Research, pages 1457–1467. PMLR, 14–18 Dec 2023.
- The waymo open sim agents challenge, 2023.
- Motion transformer with global intention localization and local movement refinement. Advances in Neural Information Processing Systems, 2022.
- Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction. In 2022 International Conference on Robotics and Automation (ICRA), pages 7814–7821, 2022.
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