Multi-Agent Reinforcement Learning for Safe Autonomous Driving Under Pedestrian Behavioral Uncertainty

In three linesJoint training of autonomous vehicle and 12 pedestrians using MARL (MAPPO) in simulation. SDC reaches 78% goal completion with 14% collision rate vs 35%/33% for rule-based baseline. Jaywalkers (13% of crossings) account for 62% of collisions. Co-training reduces collisions by 30% vs single-agent RL.

Summary generated by Claude — human-verified