WOMD-Reasoning: A Large-Scale Dataset for Interaction Reasoning in Driving

Language models uncover unprecedented abilities in analyzing driving scenarios, owing to their limitless knowledge accumulated from text-based pre-training. Naturally, they should particularly excel in analyzing rule-based interactions, such as those triggered by traffic laws, which are well documented in texts. However, such interaction analysis remains underexplored due to the lack of dedicated language datasets that address it. Therefore, we propose Waymo Open Motion Dataset-Reasoning (WOMD-Reasoning), a comprehensive large-scale Q&As dataset built on WOMD focusing on describing and reasoning traffic rule-induced interactions in driving scenarios. WOMD-Reasoning also presents by far the largest multi-modal Q&A dataset, with 3 million Q&As on real-world driving scenarios, covering a wide range of driving topics from map descriptions and motion status descriptions to narratives and analyses of agents’ interactions, behaviors, and intentions. To showcase the applications of WOMD-Reasoning, we design Motion-LLaVA, a motion-language model fine-tuned on WOMD-Reasoning. Quantitative and qualitative evaluations are performed on WOMD-Reasoning dataset as well as the outputs of Motion-LLaVA, supporting the data quality and wide applications of WOMD-Reasoning, in interaction predictions, traffic rule compliance plannings, etc. The dataset and its vision modal extension are available on this https URL. The codes & prompts to build it are available on this https URL.

Recommended citation: @misc{li2025womdreasoninglargescaledatasetinteraction, title={WOMD-Reasoning: A Large-Scale Dataset for Interaction Reasoning in Driving}, author={Yiheng Li and Cunxin Fan and Chongjian Ge and Zhihao Zhao and Chenran Li and Chenfeng Xu and Huaxiu Yao and Masayoshi Tomizuka and Bolei Zhou and Chen Tang and Mingyu Ding and Wei Zhan}, year={2025}, eprint={2407.04281}, archivePrefix={arXiv}, primaryClass={cs.RO}, url={https://arxiv.org/abs/2407.04281}, }
Download Paper