SOURCE-LINKED INTELLIGENCE
Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation
The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the trajectories of existing agents in a traffic scenario using simplified adversarial objectives to induce safety-critical interactions, which can limit the plausibility and diversity of the generated scenarios. Although inserting new adversarial vehicles can alleviate this limitation, determining when and where to introduce them in a scenario-specific manner remains challenging. In this work, we introduce \underline{CO}llision \underline{S}napsh
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-06T07:18:07.000Z
First collected: 2026-09-20T21:12:06.801Z. This is not the publication date.