管理评论 ›› 2022, Vol. 34 ›› Issue (5): 281-289.

• 应急管理 • 上一篇    下一篇

隧道行人安全流率研究

廖灿1, 郭海湘1, 诸克军1, 唐健1,2   

  1. 1. 中国地质大学(武汉)经济管理学院, 武汉 430074;
    2. 西南大学经济管理学院, 重庆 400715
  • 收稿日期:2018-03-13 出版日期:2022-05-28 发布日期:2022-06-17
  • 通讯作者: 郭海湘(通讯作者),中国地质大学(武汉)经济管理学院教授,博士。
  • 作者简介:廖灿,中国地质大学(武汉)经济管理学院博士研究生;诸克军,中国地质大学(武汉)经济管理学院教授,博士;唐健,西南大学经济管理学院讲师,博士
  • 基金资助:
    国家自然科学基金项目(71473232;71573237;71874165);教育部新世纪优秀人才支持计划项目(NCET-13-1012);教育部人文社会科学研究规划项目(15YJA630019);国家社会科学基金重点项目(19AJY015);重庆市社会科学规划项目(2019QNGL35)。

Research on the Safe Flow Rate of Tunnel Pedestrians

Liao Can1, Guo Haixiang1, Zhu Kejun1, Tang Jian1,2   

  1. 1. School of Economics and Management, China University of Geosciences(Wuhan), Wuhan 430074;
    2. College of Economics and Management, Southwest University, Chongqing 400715
  • Received:2018-03-13 Online:2022-05-28 Published:2022-06-17

摘要: 当前行人流研究主要集中在危险发生之后疏散过程的优化,危险发生之前密集行人流的管理却少有关注。本文建立了隧道行人流多智能体仿真模型,模型依据行人离出口的距离以及单元格的拥挤程度定义行人获得的效用;然后,采用贝叶斯纳什均衡,找出每个行人预期效用最大的单元格并作为其移动的目标;接着,以某隧道行人流数据为背景,对模型有效性进行验证;最后,通过多场景仿真实验,并综合考虑行人的行走倾向,得出了隧道行人安全流率与隧道宽度之间的定量关系,即隧道宽度每增加1m,安全流率增长约3人/s。本文提出的模型可以很好地模拟密集状况下行人流,研究结论可为密集行人流管理提供参考。

关键词: 隧道行人, 贝叶斯纳什均衡, 行人流仿真, 安全流率

Abstract: Existing researches on pedestrian flows have mainly focused on evacuation optimization during or after emergencies, with little attention paid to crowd management before emergencies. This research formulates a simulation model of pedestrian flow based on a multi-agent system, with the utility that each pedestrian gets in the model defined on the distance to the exit and the density of the cell. Then, Bayesian-Nash Equilibrium is employed to search for the target cell of maximum expected utility. After that, the model is validated by a real scenario and is found to have a good consistency. At last, with the experimental data collected from the different scenarios and the walking preferences taken into consideration, this paper reaches the conclusion that the safe flow rate increases by about 3ped/s as the tunnel width expands by 1m. The model proposed in this paper is proved to be working very well on dense pedestrian flows, and the conclusion would provide reference for the management of dense pedestrian flows.

Key words: tunnel pedestrians, Bayesian-Nash Equilibrium, simulation of pedestrian flow, safe flow rate