How corner is a corner case? Percentile control for highway scenario generation
Generating corner-case scenarios with appropriate adversity in a simulation environment is critical for testing an autonomous vehicle (AV) software stack's safety performance before deployment.
ProofPaper ↗
Key points
- Existing autonomous-driving scenario generators can enforce specific behavior, adversity, or feasibility conditions, but they provide limited control over how extreme a generated scenario is relative to plausible futures in the same traffic context.
- This study represents the adversity of a generated scenario as its percentile in the conditional distribution of future risk given the observed history.
- This view supports calibrated answers to two questions: how "corner" a generated corner-case scenario is and how its "cornerness" can be fine-tuned.
- We then use a percentile-conditioned joint diffusion model with sampling-time risk guidance to generate multi-agent futures, together with a reference-based criterion for evaluating percentile realization.
Sources (1)
- [1]How corner is a corner case? Percentile control for highway scenario generationHugging Face Daily Papers · Oct 4, 12:00 AM
Generating corner-case scenarios with appropriate adversity in a simulation environment is critical for testing an autonomous vehicle (AV) software stack's safety performance before deployment.
Existing autonomous-driving scenario generators can enforce specific behavior, adversity, or feasibility conditions, but they provide limited control over how extreme a generated scenario is relative to plausible futures in the same traffic context.
Extractive summary: sentences quoted from the sources.