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ZHU Minqing, GAO Jie, CUI Hongjun, MA Xinwei. Spatio-Temporal Impact of Station-area Built Environment on Urban Rail Transit Passenger Flow Based on GTWR[J]. Journal of Beijing University of Technology, 2024, 50(6): 724-732. DOI: 10.11936/bjutxb2022090010
Citation: ZHU Minqing, GAO Jie, CUI Hongjun, MA Xinwei. Spatio-Temporal Impact of Station-area Built Environment on Urban Rail Transit Passenger Flow Based on GTWR[J]. Journal of Beijing University of Technology, 2024, 50(6): 724-732. DOI: 10.11936/bjutxb2022090010

Spatio-Temporal Impact of Station-area Built Environment on Urban Rail Transit Passenger Flow Based on GTWR

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  • Received Date: September 13, 2022
  • Revised Date: February 21, 2023
  • Available Online: May 08, 2024
  • The influencing factors of rail transit passenger flow are a focus of rail transit research. The spatio-temporal nonstationarity of passenger flow at different stations was considered to be related to the built environment of station area. A spatio-temporal geographically and temporally weighted regression (GTWR) model was constructed to reveal the impacts of land diversity, density and site attributes on Tianjin rail transit passenger flow in time and space dimensions. Results show that compared with the traditional geographically weighted regression (GWR) model and ordinary least squares (OLS) model, the GTWR model has better goodness of fit. The density of bus stations promotes the passenger flow of rail transit, especially in the morning and evening rush hour of working day and the location of central city. Business facilities in the city centre attract more subway passengers at workday evening peaks, while in the suburbs they attract more subway passengers at morning peaks. Population density promotes passenger flow in rail transit. Adequate parking facilities can attract more rail passengers.

  • [1]
    LI Y, YANG L, SHEN H, et al. Modeling intra-destination travel behavior of tourists through spatio-temporal analysis[J]. Journal of Destination Marketing & Management, 2019, 11: 260-269.
    [2]
    QIAN X. The passenger transfer characteristic analysis of shenyang subway based on comparative analysis method[C]//Applied Mechanics and Materials. Durnten-Zurich: Trans Tech Publications Ltd, 2015: 484-487.
    [3]
    CHAI S, LIANG Q, ZHONG S. Design of urban rail transit network constrained by urban road network, trips and land-use characteristics[J]. Sustainability, 2019, 11(21): 6128. doi: 10.3390/su11216128
    [4]
    郭瑞利, 黄正东. 基于空间计量模型的武汉市轨道交通站点客流影响因素多级效应研究[J]. 现代城市研究, 2022(2): 118-124. https://www.cnki.com.cn/Article/CJFDTOTAL-XDCS202202017.htm

    GUO R L, HUANG Z D. Research on multi-level effects of influencing factors of passenger flow in Wuhan rail transit station based on spatial econometric model[J]. Modern Urban Research, 2022(2): 118-124. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XDCS202202017.htm
    [5]
    张佳. 城市轨道交通初期客流时空演变及影响因素研究[D]. 西安: 长安大学, 2017.

    ZHANG J. Study on the spatial-temporal evolution and influencing factors of passenger flow in the early stage of urban rail transit[D]. Xi'an: Chang'an University, 2017. (in Chinese)
    [6]
    DING C, CHEN P, JIAO J. Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: a machine learning approach[J]. Accident Analysis & Prevention, 2018, 112: 116-126.
    [7]
    李国强. 建成环境对轨道交通站点客流及接驳方式的影响研究[D]. 南京: 东南大学, 2019.

    LI G Q. Built environment, site of rail transit passenger flow and the influence of joint operation research[D]. Nanjing: Southeast University, 2019. (in Chinese)
    [8]
    CHOI J, LEE Y J, KIM T, et al. An analysis of metro ridership at the station-to-station level in Seoul[J]. Transportation, 2012, 39(3): 705-722. doi: 10.1007/s11116-011-9368-3
    [9]
    SUNG H, OH J T. Transit-oriented development in a high-density city: identifying its association with transit ridership in Seoul, Korea[J]. Cities, 2011, 28(1): 70-82. doi: 10.1016/j.cities.2010.09.004
    [10]
    PAN H, LI J, SHEN Q, et al. What determines rail transit passenger volume? Implications for transit oriented development planning[J]. Transportation Research Part D: Transport and Environment, 2017, 57D(12): 52-63.
    [11]
    JUN M J, CHOI K, JEONG J E, et al. Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul[J]. Journal of Transport Geography, 2015, 48(10): 30-40.
    [12]
    马晓磊, 张继宇, 刘剑锋, 等. 地铁站点客流特征与土地利用关系研究[J]. 都市快轨交通, 2017, 30(6): 33-38. https://www.cnki.com.cn/Article/CJFDTOTAL-DSKG201706014.htm

    MA X L, ZHANG J Y, LIU J F, et al. Study on the relationship between passenger flow characteristics and land use at subway stations[J]. Urban Rapid Rail Transit, 2017, 30(6): 33-38. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DSKG201706014.htm
    [13]
    甘佐贤. 建成环境对城市轨道交通客流及出行特征的影响机理研究[D]. 南京: 东南大学, 2019.

    GAN Z X. Built environment on the urban rail transit passenger flow and trip characteristics, the influence mechanism research[D]. Nanjing: Southeast University, 2019. (in Chinese)
    [14]
    CARDOZO O D, GARCIA-PALOMARES J C, GUTIERREZ J. Application of geographically weighted regression to the direct forecasting of transit ridership at station-level[J]. Applied Geography, 2012, 34: 548-558.
    [15]
    ZHU Y, CHEN F, WANG Z, et al. Spatio-temporal analysis of rail station ridership determinants in the built environment[J]. Transportation, 2019, 46(6): 2269-2289.
    [16]
    马新卫, 季彦婕, 金雨川, 等. 基于时空地理加权回归的共享单车需求影响因素分析[J]. 吉林大学学报(工学版), 2020, 50(4): 1344-1354. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY202004023.htm

    MA X W, JI Y J, JIN Y C, et al. Analysis of influencing factors of bike-sharing demand based on spatio-temporal geographically weighted regression[J]. Journal of Jilin University (Engineering and Technology Edition), 2020, 50(4): 1344-1354. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY202004023.htm
    [17]
    SHI Z, ZHANG N, LIU Y, et al. Exploring spatiotemporal variation in hourly metro ridership at station level: the influence of built environment and topological structure[J]. Sustainability, 2018, 10(12): 4564.
    [18]
    LAZARUS J, POURQUIER J C, FENG F, et al. Bikesharing evolution and expansion: understanding how docked and dockless models complement and compete—a case study of san francisco[R]. Berkeley: University of California, Berkeley, 2019.
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