Study on the Evolution of Passenger–Train Cooperative Urban Rail Transit Flow under Abnormal Operating Modes

Abstract Under emergencies or fault disruptions, dynamic changes in the passenger–train coordination relationship are encountered by urban rail transit systems, which can easily lead to abnormal passenger congestion and systemic overcrowding, affecting service reliability and operational efficiency. To study the spatiotemporal evolution patterns of passenger flow under abnormal operational modes, factors such as time delays and transfer burdens are considered by introducing a degraded utility function and path familiarity preference model. A limited rationality Path Re-selection model influenced by multi-source data is constructed to reveal the path re-selection behavior of passengers during abnormal operations caused by sudden events. At the same time, a passenger–train coordinated passenger flow simulation model is constructed, considering operational modes, train intervals, and dynamic passenger travel paths. The proposed model is verified through simulation experiments using the Hangzhou Metro as a case study. The results show that passengers' Path Re-selection behavior under abnormal operational modes exhibits limited rationality characteristics. As the severity of abnormal operations increases, the rate of path re-selection significantly rises, leading to a decrease in passenger flow at core stations and a transfer of flow to adjacent sections. The intensity and range of Passenger Flow Propagation also expand simultaneously. Further analysis reveals that limited rationality in path re-selection accelerates the propagation process of passenger flow, enhances its spread intensity, extends its impact range, and shortens the response delay, thereby significantly altering the spatiotemporal evolution patterns of passenger flow.