SMamba-DDPG trains separate policies on Argoverse 2 safety-critical interactions to reproduce pedestrian avoidance, finding faster reactions, lower speeds, and fewer conflicts with AVs than HDVs.
arXiv preprint arXiv:2006.04218
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Modeling Vehicle-Type-Specific Pedestrian Crash Avoidance Behavior in Safety-Critical Interactions Using Smooth-Mamba Deep Reinforcement Learning
SMamba-DDPG trains separate policies on Argoverse 2 safety-critical interactions to reproduce pedestrian avoidance, finding faster reactions, lower speeds, and fewer conflicts with AVs than HDVs.