CARS integrates responsibility attribution into adversarial scenario generation to produce physically feasible collisions with high attribution rates under regulation-prescribed driver models for autonomous vehicle testing.
RX r=1 ∇θ logp θ(τ r−1 a |τ r a ,c)R(τ 0 a ,c) # .(S14) The clipped PPO surrogate loss is Lπ(θ) =−E
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Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles
CARS integrates responsibility attribution into adversarial scenario generation to produce physically feasible collisions with high attribution rates under regulation-prescribed driver models for autonomous vehicle testing.