上海大学学报(自然科学版) ›› 2023, Vol. 29 ›› Issue (4): 694-704.doi: 10.12066/j.issn.1007-2861.2433

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基于 AnyLogic 的轨道交通车站大客流瓶颈识别与疏散组织优化 

陈雷钰, 张汝华, 马明迪   

  1. 山东大学 齐鲁交通学院, 山东 济南 250012
  • 收稿日期:2022-06-22 出版日期:2023-08-30 发布日期:2023-09-01
  • 通讯作者: 张汝华 (1969—), 男, 副教授, 博士, 研究方向为交通运输系统规划设计与管理.
  • 基金资助:
    国家重点研发计划资助项目 (2022YFE0104300)

Anylogic-based bottleneck identification and evacuation organization optimization of large passenger flow in rail transit stations 

CHEN Leiyu, ZHANG Ruhua, MA Mingdi   

  1. School of Qilu Transportation, Shandong University, Jinan 250012, Shandong, China
  • Received:2022-06-22 Online:2023-08-30 Published:2023-09-01

摘要:

以济南园博园地铁站为研究对象, 通过分析行人在不同设备设施处的行为特性, 建立 行人流模型, 运用 AnyLogic 软件搭建仿真实验平台, 针对 3 种不同类型的大客流情况进行紧 急疏散模拟. 仿真结果表明: 在发生可预见性大客流情况下, 当车站客流增加幅度较小时, 站台层客流密度较大, 可通过缩短列车运行间隔来提高车站疏散能力; 而车站客流大幅增加时,车站安检区域发生拥堵, 需增设一条安检通道. 在发生不可预见性大客流时, 车站大多数情况下都能满足疏散标准, 但楼梯通道和出站闸机处仍是客流瓶颈所在, 故高峰期客流疏散需要人 为采取一定措施合理引导. 通过模拟 2 种类型大客流情况下的车站应急疏散过程, 识别出车站的瓶颈, 并对瓶颈做出有效改善措施, 对保障乘客疏散安全和效率、提高车站服务能力及制订 应急疏散方案具有重要意义.

关键词: 地铁车站, 应急疏散, 瓶颈识别, 疏散优化, AnyLogic

Abstract:

This study takes Jinan Yuanboyuan Metro Station as the research object and establishes a pedestrian flow model by analyzing the behavior characteristics of pedestrians at different equipment and facilities. AnyLogic software is used to build a simulation experiment platform to simulate emergency evacuation for three different types of large passenger flow situations. The simulation results reveal the following: In the case of predictable large passenger flow, when the increase in station passenger flow is small, the passenger flow density on the platform layer is large, and the evacuation capacity of the station can be improved by shortening the train running interval. When the station passenger flow increases significantly, the station security check area is congested, and a security check channel needs to be added. In the event of unpredictable large passenger flow, the station can meet the evacuation standards in most cases, but the stairway and exit gate are still the bottleneck of passenger flow; therefore, the evacuation of passenger flow during peak hours needs to be guided by certain measures. By simulating the emergency evacuation process under two large passenger flow conditions, the bottleneck of the station is identified, and effective measures are taken to improve it, which is of great significance to ensure the safety and efficiency of passenger evacuation, improve station service capacity, and formulate the emergency evacuation plan. 

Key words: subway stations, emergency evacuation, bottleneck identi?cation, evacuation optimization, AnyLogic

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