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<p>In large-scale metro interchange stations, significant passenger flow volumes during peak hours are prone to induce pedestrian congestion phenomena, presenting operational challenges. Taking Metro S transfer station as the research object, this study constructs an AnyLogic pedestrian simulation platform based on the social force model to simulate the current passenger flow conditions in the station concourse area, identifying key bottleneck zones. By employing an optimization method that integrates passenger flow guidance with coordinated allocation of equipment resources, a dual-path passenger flow diversion mechanism is designed to alleviate congestion caused by intersecting passenger flow lines. The optimization results demonstrate that this approach can effectively mitigate peak-hour congestion while reducing passenger walking time and improving throughput efficiency. This offers decision support for passenger flow management in large metro transfer stations.</p>

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Simulation-based optimization analysis of passenger flow organization in metro interchange stations using AnyLogic

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月7日

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  • Yuhang Tian,
  • Guowei Jin,
  • Shizheng Lu,
  • Wenlong Ma,
  • Nan Li,
  • Guangtao Cao,
  • Wenjie Wang

摘要

In large-scale metro interchange stations, significant passenger flow volumes during peak hours are prone to induce pedestrian congestion phenomena, presenting operational challenges. Taking Metro S transfer station as the research object, this study constructs an AnyLogic pedestrian simulation platform based on the social force model to simulate the current passenger flow conditions in the station concourse area, identifying key bottleneck zones. By employing an optimization method that integrates passenger flow guidance with coordinated allocation of equipment resources, a dual-path passenger flow diversion mechanism is designed to alleviate congestion caused by intersecting passenger flow lines. The optimization results demonstrate that this approach can effectively mitigate peak-hour congestion while reducing passenger walking time and improving throughput efficiency. This offers decision support for passenger flow management in large metro transfer stations.