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考虑乘客选择行为的地铁车站承载能力瓶颈识别方法
引用本文:黄家骏,徐瑞华,邓颖,奚梦汝.考虑乘客选择行为的地铁车站承载能力瓶颈识别方法[J].同济大学学报(自然科学版),2018,46(8):1080-1088.
作者姓名:黄家骏  徐瑞华  邓颖  奚梦汝
作者单位:同济大学道路与交通工程教育部重点实验室;安诚傲林规划设计顾问(上海)有限公司
基金项目:国家自然科学基金面上项目(71271153);国家自然科学青年基金(71701152);中央高校基本科研业务费专项资金(22120170239)
摘    要:乘客选择行为引起地铁车站客流量分布动态变化,并导致拥堵的传播,是承载能力瓶颈产生的关键因素之一.通过分析乘客在站服务事件链,构建地铁车站系统中设施设备关联网络.在分析乘客选择行为作用下的关联网络特性的基础上,建立了节点约束下的车站客流分配模型,并引入动态惩罚函数求解该模型,结合求解结果,提出通过节点受影响程度指标来识别能力瓶颈.以上海地铁陆家浜路站为例分析,与StaPass软件的仿真结果进行对比,验证了该方法的可行性和准确性,有助于快速分析不同客流条件下车站客流分布,并确定能力瓶颈.

关 键 词:地铁网络    承载能力瓶颈  设施设备关联网络  乘客选择行为  客流分配模型  动态惩罚函数
收稿时间:2017/9/15 0:00:00
修稿时间:2018/6/11 0:00:00

Identification of Bottleneck for Passenger Transport Capacity of Metro Station Considering Passenger Choice Behavior
HUANG Jiajun,XU Ruihu,DENG Ying and XI Mengru.Identification of Bottleneck for Passenger Transport Capacity of Metro Station Considering Passenger Choice Behavior[J].Journal of Tongji University(Natural Science),2018,46(8):1080-1088.
Authors:HUANG Jiajun  XU Ruihu  DENG Ying and XI Mengru
Institution:Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China,Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China,Hyder ACLA Consulting(Shanghai)Limited, Shanghai 200051, China and Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China
Abstract:Passenger choice behavior, which causes dynamic changes of the passenger flow distribution and leads to the spread of congestion, is one of the key factors of bottleneck for passenger transport capacity. An association network of facilities is set up based on the analysis of passenger service chain in station. Then the passenger flow distribution model with node capacity constraints is established considering the passenger choice behavior. The dynamic penalty function is introduced to solve this model. Based on the result of the solution, the identification of bottleneck for passenger transport capacity through the index of affected degree of nodes is proposed. Finally, a case study of Lujiabang Road Station in Shanghai is carried out and compared with the simulation results of StaPass, verifying the feasibility and accuracy of this approach, which can help to analyze the passenger flow distribution of metro station in different scenarios.
Keywords:metro network  bottleneck for passenger transport capacity  association network of facilities  passenger choice behavior  passenger flow distribution model  dynamic penalty function
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