登录    注册    个人中心    ENGLISH
   
过刊检索
年份
《城市交通》杂志
2021年 第2期
城市轨道交通乘客换乘决策因素分析
点击量:346

文章编号: 1672-5328(2021)02-0121-07

李艺1,施澄2,邹智军1
(1. 同济大学道路与交通工程教育部重点实验室,上海201804;2. 同济大学建筑与城市规划学院,上海201804)

摘要: 许多城市的轨道交通系统已经完成从单线运营到多线网络化运营的转变。伴随网络化发展而 来的集中换乘客流,给轨道交通的规划建设与安全运营提出了挑战。以上海市轨道交通为例,通过 对比手机信令与客流分配模型两种统计途径下的换乘客流差异,探究乘客换乘行为特征与换乘决策 影响因素。将绕行换乘行为归纳为6 类:高辨识度换乘车站、换乘不便捷车站、多功能复合型车 站、长距离少换乘、避免拥堵和纸面地图误导。考虑轨道交通换乘站自身属性,对未来城市轨道交 通客流分配模型提出改进方向,为轨道交通网络规划提供参考。

关键词: 轨道交通规划;网络化;换乘;手机信令数据;客流分配模型

中图分类号: U491

文献标识码:A

Decision-Making Factor Analysis of Urban Rail Transit Transfer Flow

Li Yi1, Shi Cheng2, Zou Zhijun1
(1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education of Tongji University, Shanghai 201804, China; 2. College of Architecture and Urban Planning of Tongji University, Shanghai 201804, China)

Abstract: Many urban rail transit systems have complete the transformation from single-line operation to multi-line rail network. With the expansion of the urban rail transit network, the centralized passenger flow brings challenges to urban rail transit system in the aspects of planning, construction, operation and management. Taking urban rail transit in Shanghai as an example, this paper discusses the characteristics of passengers' transfer behavior and the influence factors of transfer decision mechanisms through comparing the difference of passenger flow under the two statistical approaches of cellular signaling and passenger flow distribution model. The behavior of detour transfer can be divided into six categories: high identification transfer station, unconventional transfer station, multi- functional transfer station, long-distance and less transfer, and avoiding congestion and misleading of maps. Considering the characteristics of rail transfer stations, the paper provides suggestions on future urban rail transit passenger flow assignment model so as to improve urban rail transit network planning.

Keywords: urban rail transit planning; network; transfer; cellular signaling data; passenger flow assignment model