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Simulation study demonstrates enhanced discovery of safety-critical events across automated vehicle planners, indicating more controlled adversarial evaluation.
Closed-loop safety evaluation requires traffic agents that expose planner weaknesses without producing arbitrary behavior. Existing adversarial tests often couple behavior generation, risk search, and failure counting, limiting control over how interactions are created and whether repeated events constitute new evidence. Style2Risk uses interaction style as an explicit control interface. Assertiveness and courtesy condition a Gaussian behavior prior, while a bounded residual directs the controlled participant toward the tested planner. Protocol screens retain interactions that satisfy declared action and trajectory constraints, and a style–interaction–event archive separates discovery breadth from repeated observations. We evaluate seven configurations and three planners in 31,500 WOMD–Waymax rollouts. Relative to strict no-style, Style2Risk increases protocol-valid safety-critical events from 110.0 to 258.0 per 500-scenario planner chunk and expands occupied archive cells from 28 to 33. A common trajectory evaluator that does not call the generating prior reports a 1.343 m reduction in joint displacement error, a 0.163 increase in interaction consistency, and a 0.037 reduction in collision rate. A separate 26-scenario experiment assigns style from pre-rollout information and evaluates online archive guidance. The results support style-conditioned control as a practical mechanism for targeted closed-loop testing and explicit evidence accounting.
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Lai et al. (2026) studied this question.
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