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Why do passengers choose a specific car of a metro train during the morning peak hours?

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  • Kim, Hyunmi
  • Kwon, Sohee
  • Wu, Seung Kook
  • Sohn, Keemin

Abstract

Crowding on metro trains is an important measure of passenger satisfaction and also provides a criterion for determining service frequency and the number of cars necessary for a train set. Particularly in metropolitan areas during morning peak hours, many studies have revealed a considerable difference in the crowding of specific cars on a single train. To accommodate the impact of this phenomenon in calculating metro capacity, a loading diversity factor has been adopted in many transportation studies. However, the underlying causes behind the uneven nature of carriage loading have rarely been examined in a systematic manner. In particular, there has been no trial to explain the nature of choice within a framework for individual passengers. Under the assumption that the uneven selection might stem from each passenger’s intrinsic preference for a specific car, the present study established a nested logit model to investigate the potential factors affecting the choice of a specific car on a train. Passengers were interviewed as they boarded from the platforms of line 7 of the Seoul Metro during the morning peak hours. Results show that the motivation to minimize the walking distance at destination stations turned out to be the most decisive in determining a passenger’s choice for a specific car of a train.

Suggested Citation

  • Kim, Hyunmi & Kwon, Sohee & Wu, Seung Kook & Sohn, Keemin, 2014. "Why do passengers choose a specific car of a metro train during the morning peak hours?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 249-258.
  • Handle: RePEc:eee:transa:v:61:y:2014:i:c:p:249-258
    DOI: 10.1016/j.tra.2014.02.015
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    References listed on IDEAS

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    Cited by:

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    2. Gao, Fan & Han, Chunyang & Yang, Linchuan & Liang, Jian & He, Xuan & Li, Fan, 2024. "Analyzing spatiotemporal distribution patterns of metro ridership: Comparison between common-class and business-class carriage service," Journal of Transport Geography, Elsevier, vol. 115(C).
    3. Hänseler, Flurin S. & van den Heuvel, Jeroen P.A. & Cats, Oded & Daamen, Winnie & Hoogendoorn, Serge P., 2020. "A passenger-pedestrian model to assess platform and train usage from automated data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 948-968.
    4. Junghan Baek & Keemin Sohn, 2016. "An investigation into passenger preference for express trains during peak hours," Transportation, Springer, vol. 43(4), pages 623-641, July.
    5. Jie Yang & Nirajan Shiwakoti & Richard Tay, 2023. "Exploring Melbourne Metro Train Passengers’ Pre-Boarding Behaviors and Perceptions," Sustainability, MDPI, vol. 15(15), pages 1-20, July.
    6. Liudan Jiao & Liyin Shen & Chenyang Shuai & Yongtao Tan & Bei He, 2017. "Measuring Crowdedness between Adjacent Stations in an Urban Metro System: a Chinese Case Study," Sustainability, MDPI, vol. 9(12), pages 1-14, December.
    7. Yizhou Zhang & Erik Jenelius & Karl Kottenhoff, 2017. "Impact of real-time crowding information: a Stockholm metro pilot study," Public Transport, Springer, vol. 9(3), pages 483-499, October.
    8. Zhuangbin Shi & Ning Zhang & Yang Liu & Wei Xu, 2018. "Exploring Spatiotemporal Variation in Hourly Metro Ridership at Station Level: The Influence of Built Environment and Topological Structure," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
    9. Muñoz, Juan Carlos & Soza-Parra, Jaime & Didier, Arturo & Silva, Constanza, 2018. "Alleviating a subway bottleneck through a platform gate," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 446-455.
    10. Cats, Oded & West, Jens & Eliasson, Jonas, 2016. "A dynamic stochastic model for evaluating congestion and crowding effects in transit systems," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 43-57.

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