AINeutralarXiv – CS AI · 7h ago6/10
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Simulation of collision avoidance behavior in crowd movement by data-driven approach
Researchers propose CPGAN, a collision-penalized generative adversarial network that improves crowd simulation accuracy by incorporating pedestrian collision mechanisms directly into the model's loss function. The approach significantly reduces collision rates in bidirectional pedestrian flows while accurately reproducing real-world phenomena like lane formation.