STRIDE-QA-Mini is a question-answering dataset for autonomous driving, designed to study the spatiotemporal reasoning capabilities of visual language models (VLMs) in autonomous driving scenarios. The dataset contains 103,220 question-answer pairs and 5,539 image samples. The data is derived from real dashcam footage collected in Tokyo (urban, suburban, and highway environments, in various weather conditions).

Dataset structure

• Object-centric Spatial Question Answering (19,895 question-answer pairs): Relationship between two external vehicles
• Egocentric Spatial Question Answering (54,390 question-answer pairs): The relationship between the own vehicle and another vehicle
• Egocentric Spatiotemporal Question Answering (28,935 question-answer pairs): Future distance and direction prediction task

Citation

@misc{strideqa2025, title={STRIDE-QA: Visual Question Answering Dataset for Spatiotemporal Reasoning in Urban Driving Scenes}, author={Keishi Ishihara and Kento Sasaki and Tsubasa Takahashi and Daiki Shiono and Yu Yamaguchi}, year={2025}, eprint={2508.10427}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2508.10427}, }