CCDiff masks diffusion guidance to top-ranked agents selected by a time-to-collision based causal graph, and reports better controllability-realism tradeoffs than prior traffic simulators.
A survey on safety-critical driving scenario generation—a methodological per- spective
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Causal Composition Diffusion Model for Closed-loop Traffic Generation
CCDiff masks diffusion guidance to top-ranked agents selected by a time-to-collision based causal graph, and reports better controllability-realism tradeoffs than prior traffic simulators.