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arXiv AI By Shucheng Zhang, Yuang Zhang, Bingzhang Wang, Muhammad Monjurul Karim, Kehua Chen, Yinhai Wang

CrashDiffuser: VLM-Guided Collision Intent Reasoning for Fine-Grained Safety-Critical Traffic Scenario Generation

Read the original on arXiv AI →

CrashDiffuser is a closed-loop VLM‑guided diffusion framework designed for fine‑grained safety‑critical traffic scenario generation. It separates semantic collision reasoning from trajectory synthesis via a hierarchical collision‑intent interface that specifies target contact regions (head, rear, or side). The system uses a vision‑language model to extract scene context and predict structured action tuples, which condition a diffusion model to produce executable adversarial trajectories, achieving high target‑collision and contact‑region control rates on WOMD‑derived scenarios.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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