Influence of TOD Modes on Passenger Travel Behavior in Urban Rail Transit Systems

被引:0
|
作者
Xiaohong Li
Qiming Xiao
Yadi Zhu
Yuting Yang
机构
[1] Beijing Jiaotong University,School of Civil Engineering
[2] Jinhua Traffic Engineering Management Center,undefined
来源
Urban Rail Transit | 2022年 / 8卷
关键词
Urban rail transit; TOD; Travel behavior; Self-selection behavior; Cluster analysis; Propensity score matching;
D O I
暂无
中图分类号
学科分类号
摘要
Transit-oriented development (TOD) mode refers to the integrated development of high-density and multi-functional land in the vicinity of core public transportation stations to increase public transportation rates and address problems such as traffic congestion and land shortages. Therefore, it is crucial to comprehend the relationship between TOD areas and the travel behavior of rail transit residents. However, the income level and occupation of residents have a significant impact on their travel behavior, as people tend to choose their residential, work, and entertainment areas based on their economic characteristics. This paper focuses primarily on two aspects: how to distinguish TOD areas from non-TOD areas (specifically, rail stations) and the variations in the travel behavior of the people residing in these areas. Rail stations were first classified via cluster analysis according to the selected TOD indexes; then, a propensity score matching method was applied to control the influence of self-selection behavior. Based on this, the matched results were analyzed to study the difference in the travel behavior characteristics of residents in TOD and non-TOD areas. The results indicate that residents in TOD areas are more likely to travel by public transportation than those from non-TOD areas. The findings of this study promote a people-oriented urban planning concept and would have practical implications for applications of TOD modes on urban public transportation systems.
引用
收藏
页码:175 / 183
页数:8
相关论文
共 50 条
  • [21] Analysis of Passenger Queuing Behavior on Urban Rail Transit Platform during Rush Hour
    Zhang, Ying
    Song, Rui
    Hao, Na
    SUSTAINABLE CITIES DEVELOPMENT AND ENVIRONMENT PROTECTION, PTS 1-3, 2013, 361-363 : 1927 - 1932
  • [22] Research on the Rail Transit Station Spacing Based on Passenger Travel Choice
    Dai, Qiqi
    Li, Yuanfu
    Wang, Fang
    Wang, Ying
    ADVANCED TRANSPORTATION, PTS 1 AND 2, 2011, 97-98 : 327 - +
  • [23] Research on TOD Planning of Urban Rail Transit Based on Cellular Automata
    Ma, Dandan
    Chen, Yiwen
    2019 4TH INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION (ICECTT 2019), 2019, : 332 - 335
  • [24] Measures of Travel Reliability on an Urban Rail Transit Network
    Liu, Jie
    Schonfeld, Paul M.
    Peng, Qiyuan
    Yin, Yong
    JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2020, 146 (06)
  • [25] Model of Passenger Route Choice in the Urban Rail Transit Network
    Qiao Ke
    Zhao Peng
    Qin Zhi-peng
    PROCEEDINGS OF 2ND CONFERENCE ON LOGISTICS, INFORMATICS AND SERVICE SCIENCE (LISS 2012), VOLS 1 AND 2, 2013,
  • [26] Standing Passenger Density of Urban Rail Transit Based on Tolerance
    Chen W.
    Li Z.-P.
    Yu D.-B.
    Ju Y.-N.
    Yin J.-C.
    Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2020, 20 (02): : 225 - 230and243
  • [27] Passenger Traffic Organization Method of Urban Rail Transit Interchange
    Cao, Rui
    Ma, Chaoqun
    Wang, Zhaofei
    CICTP 2019: TRANSPORTATION IN CHINA-CONNECTING THE WORLD, 2019, : 6299 - 6310
  • [28] Collaborative passenger flow control for an urban rail transit network
    Zhao, Qingqing
    Tang, Jinjin
    Zhang, Xin
    COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2024, 39 (01) : 63 - 85
  • [29] Urban Rail Transit Passenger Flow Forecasting-XGBoost
    Sun, Xiaoli
    Zhu, Caihua
    Ma, Chaoqun
    CICTP 2022: INTELLIGENT, GREEN, AND CONNECTED TRANSPORTATION, 2022, : 1142 - 1150
  • [30] Passenger flow forecasting approaches for urban rail transit: a survey
    Xue, Qiuchi
    Zhang, Wei
    Ding, Meiling
    Yang, Xin
    Wu, Jianjun
    Gao, Ziyou
    INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2023, 52 (08) : 919 - 947