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Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices

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  • Zhenjun Zhu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, China)

  • Jun Zeng

    (School of Transportation, Southeast University, No.2 Dongnandaxue Road, Nanjing 211189, China)

  • Xiaolin Gong

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, China)

  • Yudong He

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, China)

  • Shucheng Qiu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, China)

Abstract

With the continuous improvement of the operation line network of urban rail transit, analyzing influencing factors of transfer passenger flow of urban rail transit is critical to improve the transfer demand analysis of urban rail transit. Using data collected from questionnaires, transfer passenger flow surveys and smart cards, this study proposes an approach base on nested logit passenger flow assignment model considering transfer choice behaviours of passengers. The transfer passenger flow at seven transfer stations in Nanjing is obtained. Subsequently, this study investigates the potential influencing factors of transfer passenger flow, including the node degree, geographic location (located in the city center, urban fringe, suburbs or suburban fringe), economic location (distance from the city center) and transportation locations (if it is close to a transportation hub or in combination with the hub) of rail transit transfer stations. The results indicate that a positive correlation between the transfer passenger flow and the node degrees of transfer stations. However, the relationship between transfer passenger flow and the economic, geographic, and transportation locations of transfer stations is not clear. The finding have reference value for the network design of rail transit transfer stations and transfer facilities, and provide reference for the analysis of passenger flow under network operation.

Suggested Citation

  • Zhenjun Zhu & Jun Zeng & Xiaolin Gong & Yudong He & Shucheng Qiu, 2021. "Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:16:p:8462-:d:612031
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    References listed on IDEAS

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    Cited by:

    1. Ming Li & Wei Yu & Jun Zhang, 2023. "Clustering Analysis of Multilayer Complex Network of Nanjing Metro Based on Traffic Line and Passenger Flow Big Data," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    2. Xiaona Zhang & Fu Wang & Weidi Xu & Yin Wang & Jingwen Luo & Xinyu Chen & Manqing Ye, 2023. "Research on the Evaluation of Rail Transit Transfer System Based on the Time Value," Sustainability, MDPI, vol. 16(1), pages 1-25, December.

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