nuReasoning Project website nuReasoning is a reasoning centric multimodal autonomous driving dataset for evaluating and training end to end driving systems in long tail real world scenarios. Each sample is built around a driving clip with synchronized multi camera images, LiDAR data, ego state, object annotations, HD map, routing, and frame level reasoning annotations. Reasoning annotations are organized into three complementary fields: Spatial Reasoning : structured scene context, 2D and 3D detections, object relations, map projections, ego frame object future states, and potential future conflicts. Decision Reasoning : scene interpretation, critical components, driving decisions, and causal reasoning traces. Counterfactual Reasoning : alternative actions, risk levels, safety outcomes, and explanations of why unsafe or suboptimal actions should be avoided. Disclaimer: Dataset access and file availability are subject to internal review, approval, and compliance requirements. Data will be progressively released as each portion completes the required compliance process. Dataset Summary Dataset name: nuReasoning Data source: Motional internal AV fleet Dataset owner: Motional AD Inc. S…
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