Industrial Engineering Journal ›› 2023, Vol. 26 ›› Issue (5): 139-148.doi: 10.3969/j.issn.1007-7375.2023.05.016

• System Modeling & Optimization Algorithm • Previous Articles     Next Articles

A Passenger Flow Simulation and Organization Optimization of Hub Stations Based on Self-learning Agent Model

FU Hui, YAO Yipeng, CHEN Saifei   

  1. School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2022-10-30 Published:2023-10-25

Abstract: In order to guarantee free passenger flows in a hub station with a given flow line, the station can adjust the facility deployment, design building structures and passenger service processes, to reduce the conflicts, so as to improve the efficiency of passenger flows and make an optimization of passenger flow organization. This paper first establishes an agent-based simulation framework to describe detailed passenger behavior in a hub station from the optimization and organization of passenger flows. Then, a passenger flow simulation for hub stations is developed based on the proposed framework, and the reliability of the proposed simulation is verified by combining real data. Finally, the optimization strategy of passenger flow organization is generated by applying the proposed simulation. Results show that the proposed agent model and its method can support the simulation of passenger flow within a hub station and simulate the movement behaviour of passengers in facilities with relatively small errors. The facility optimization strategy can save the redundant facility capacity of the inbound flow line in Guangzhou South Railway Station.

Key words: simulation framework, hub station, pedestrian flow simulation, organizational optimization

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