Improved visual-information-driven model for crowd simulation and its modular application

ArXi:2504.03758v4 Announce Type: replace-cross Crowd movement simulation is crucial for pedestrian safety management and facility design. Data-driven models offer the potential to improve realism and predictive accuracy, but most are developed for a single scenario, limiting their flexibility. We propose a data-driven crowd simulation model that incorporates refined visual-information extraction and explicit exit cues, aiming to improve flexibility across multiple scenarios by effectively capturing core navigational features.