"DriveScene: A Comprehensive Video Dataset for Scenario Understanding, Generation, and Explanation in Autonomous Driving Research"

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Authors: Shihong Ling
Cited by: 0

Abstract

"Ensuring autonomous vehicles are trustworthy and transparent is crucial for safety and public trust, especially in high-stakes emergent scenarios. However, existing driving datasets rarely capture these safety-critical situations or provide the detailed annotations needed for explainable decision-making. To address this, we introduce DriveScene, a large-scale driving video dataset covering a diverse range of scenarios from routine driving to safety-critical emergencies and featuring a comprehensive annotation schema that labels each scene\u2019s key objects, their actions, causal factors, and surrounding context. These rich annotations support several key tasks: identifying important objects for interaction-aware modeling, predicting the temporal unfolding of emergent scenarios, generating human-readable explanations of driving behavior, and modeling human perception of scenario risk for human-centered scenario analysis. "

Fields of Study & Subjects

Autonomous Vehicle Technology and Safety Human-Automation Interaction and Safety Traffic and Road Safety

Publication details

Journal / source
IEEE DataPort
Publication date
31 January 2026
Document type
Dataset