Passenger Flow Simulation Model for Urban Rail Transit Stations Based on Multipotential Fields in Three‐Dimensional Space

The spatial and temporal rules governing passenger flow in urban rail transit (URT) stations are complex, and simulation modeling and analysis of passenger flow distribution in stations are very important in regard to scientifically organizing and controlling passenger flow and improving passenger travel efficiency. With a focus on the multilevel three‐dimensional spatial structure of URT stations and the composition of multiclass passenger flow lines, the travel process and microbehavior of passengers are analyzed here. The goal‐driven behavior of passenger flow groups in the free area and the interaction between them are considered, and a static–dynamic field hybrid model describing the differences in speed between passengers, their walking, and avoidance behavior and a queue field model of queuing behavior are constructed. A selection behavior model for facility nodes such as gates, interlayer facilities, and waiting areas is constructed to represent heterogeneous passenger flow to multiservice channels. A passenger flow simulation method framework for URT stations that takes into account heterogeneous passenger flow, the 3D spatial structure, and multipotential energy field is also established. The effectiveness of the proposed model and method is verified via simulation of Changsha Metro Shumuling Station, and it is found that the proportion of escalators selected as interlayer facilities is significantly higher than that for stairs. After a train leaves the station, the passenger flow density on both sides of the platform reaches more than 1.5 person/m 2 , significantly higher than that in the central area of the platform. The average passing times for passengers at the exit gate and the ascending escalator are 16–18 and 13–14 s, respectively. The average queue length and passing times for passengers are higher than those at the entrance gate and the descending escalator. These results can provide support for decisions on the actual operation of URT stations.