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Measuring crowding-related comfort in public transport

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  • Dilay Çelebi
  • Şükrü İmre

Abstract

In this paper we focus on the estimation of crowding in public transport – specifically urban rail systems – and its effect on perceived comfort. It is different from similar studies in the method it employs for estimating crowding levels in vehicles. Specifically, we formulate a function of time and location, which uses only passenger embarking data to estimate the number of passengers in vehicles. Then we convert the estimated crowding values into perceived discomfort levels by trip section. Our method depends on hourly seasonality assumptions but provides good estimates of crowding in urban rail systems even when passenger alighting data is not available. We illustrate the implementation of our model with the example of the Istanbul Metro system.

Suggested Citation

  • Dilay Çelebi & Şükrü İmre, 2020. "Measuring crowding-related comfort in public transport," Transportation Planning and Technology, Taylor & Francis Journals, vol. 43(7), pages 735-750, October.
    • Handle: RePEc:taf:transp:v:43:y:2020:i:7:p:735-750
    DOI: 10.1080/03081060.2020.1805546
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    Cited by:

    1. Tianxing Dai & Brian D. Taylor, 2023. "Three’s a crowd? Examining evolving public transit crowding standards amidst the COVID-19 pandemic," Public Transport, Springer, vol. 15(2), pages 321-341, June.
    2. Luan, Xiaojie & Corman, Francesco, 2022. "Passenger-oriented traffic control for rail networks: An optimization model considering crowding effects on passenger choices and train operations," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 239-272.
    3. Abderrahman Ait-Ali & Jonas Eliasson, 2022. "The value of additional data for public transport origin–destination matrix estimation," Public Transport, Springer, vol. 14(2), pages 419-439, June.
    4. Chen, Xin & Jiang, Yu & Bláfoss Ingvardson, Jesper & Luo, Xia & Anker Nielsen, Otto, 2023. "I can board, but I’d rather wait: Active boarding delay choice behaviour analysis using smart card data in metro systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).

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