Station passenger flow evacuation method based on social force model and improved Dijkstra algorithm

Urban rail transit stations often encounter high passenger flow density and complex passenger behaviors, necessitating efficient evacuation strategies that consider the station's unique environmental layout and passenger dynamics. This study addresses the limitations of the social force model, particularly its inability to plan real-time evacuation routes based on the dynamic opening and closing of station exits. A novel evacuation method is proposed, integrating the social force model with an improved Dijkstra algorithm. This enhanced algorithm is capable of determining K-shortest paths for passengers to reach multiple exits, enabling passengers to access multiple evacuation exits and providing essential path information for the evacuation process. The integration of the BPR function in route allocation further enhances the method by considering both route length and congestion levels, ensuring that passengers are directed along the optimal evacuation paths. To evaluate the effectiveness of the proposed method, a simulation experiment was conducted on passenger flow evacuation in subway stations. The results validate the feasibility of the approach and highlight its potential for practical application in simulating and managing passenger flow evacuation in urban rail transit environments.