IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v95y2017icp105-125.html
   My bibliography  Save this article

Crowding cost estimation with large scale smart card and vehicle location data

Author

Listed:
  • Hörcher, Daniel
  • Graham, Daniel J.
  • Anderson, Richard J.

Abstract

Crowding discomfort is an external cost of public transport trips imposed on fellow passengers that has to be measured in order to derive optimal supply-side decisions. This paper presents a comprehensive method to estimate the user cost of crowding in terms of the equivalent travel time loss, in a revealed preference route choice framework. Using automated demand and train location data we control for fluctuations in crowding conditions on the entire length of a metro journey, including variations in the density of standing passengers and the probability of finding a seat. The estimated standing penalty is 26.5% of the uncrowded value of in-vehicle travel time. An additional passenger per square metre on average adds 11.9% to the travel time multiplier. These results are in line with earlier revealed preference values, and suggest that stated choice methods may overestimate the user cost of crowding. As a side-product, and an important input of the route choice analysis, we derive a novel passenger-to-train assignment method to recover the daily crowding and standing probability pattern in the metro network.

Suggested Citation

  • Hörcher, Daniel & Graham, Daniel J. & Anderson, Richard J., 2017. "Crowding cost estimation with large scale smart card and vehicle location data," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 105-125.
  • Handle: RePEc:eee:transb:v:95:y:2017:i:c:p:105-125
    DOI: 10.1016/j.trb.2016.10.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261516303551
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2016.10.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kim, Kyung Min & Hong, Sung-Pil & Ko, Suk-Joon & Kim, Dowon, 2015. "Does crowding affect the path choice of metro passengers?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 292-304.
    2. Lam, Terence C. & Small, Kenneth A., 0. "The value of time and reliability: measurement from a value pricing experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 231-251, April.
    3. Spiess, Heinz & Florian, Michael, 1989. "Optimal strategies: A new assignment model for transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 23(2), pages 83-102, April.
    4. Wardman, Mark & Murphy, Paul, 2015. "Passengers’ valuations of train seating layout, position and occupancy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 222-238.
    5. Haywood, Luke & Koning, Martin & Monchambert, Guillaume, 2017. "Crowding in public transport: Who cares and why?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 215-227.
    6. 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.
    7. Sumalee, Agachai & Tan, Zhijia & Lam, William H.K., 2009. "Dynamic stochastic transit assignment with explicit seat allocation model," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 895-912, September.
    8. de Palma, André & Kilani, Moez & Proost, Stef, 2015. "Discomfort in mass transit and its implication for scheduling and pricing," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 1-18.
    9. Batarce, Marco & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2016. "Valuing crowding in public transport: Implications for cost-benefit analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 358-378.
    10. Bagchi, M. & White, P.R., 2005. "The potential of public transport smart card data," Transport Policy, Elsevier, vol. 12(5), pages 464-474, September.
    11. Haywood, Luke & Koning, Martin, 2015. "The distribution of crowding costs in public transport: New evidence from Paris," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 182-201.
    12. Small, Kenneth A., 2001. "The Value of Pricing," University of California Transportation Center, Working Papers qt0rm449sx, University of California Transportation Center.
    13. Engelson, Leonid & Fosgerau, Mogens, 2011. "Additive measures of travel time variability," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1560-1571.
    14. Li, Zheng & Hensher, David A., 2011. "Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal," Transport Policy, Elsevier, vol. 18(6), pages 880-887, November.
    15. Bates, John & Polak, John & Jones, Peter & Cook, Andrew, 0. "The valuation of reliability for personal travel," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 191-229, April.
    16. van Loon, Ruben & Rietveld, Piet & Brons, Martijn, 2011. "Travel-time reliability impacts on railway passenger demand: a revealed preference analysis," Journal of Transport Geography, Elsevier, vol. 19(4), pages 917-925.
    17. Takahiko Kusakabe & Takamasa Iryo & Yasuo Asakura, 2010. "Estimation method for railway passengers’ train choice behavior with smart card transaction data," Transportation, Springer, vol. 37(5), pages 731-749, September.
    18. Prud'homme, Rémy & Koning, Martin & Lenormand, Luc & Fehr, Anne, 2012. "Public transport congestion costs: The case of the Paris subway," Transport Policy, Elsevier, vol. 21(C), pages 101-109.
    19. Mark Wardman & Gerard Whelan, 2011. "Twenty Years of Rail Crowding Valuation Studies: Evidence and Lessons from British Experience," Transport Reviews, Taylor & Francis Journals, vol. 31(3), pages 379-398.
    20. Tirachini, Alejandro & Sun, Lijun & Erath, Alexander & Chakirov, Artem, 2016. "Valuation of sitting and standing in metro trains using revealed preferences," Transport Policy, Elsevier, vol. 47(C), pages 94-104.
    21. Hamdouch, Younes & Ho, H.W. & Sumalee, Agachai & Wang, Guodong, 2011. "Schedule-based transit assignment model with vehicle capacity and seat availability," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1805-1830.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haywood, Luke & Koning, Martin & Monchambert, Guillaume, 2017. "Crowding in public transport: Who cares and why?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 215-227.
    2. Jenelius, Erik, 2018. "Public transport experienced service reliability: Integrating travel time and travel conditions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 275-291.
    3. Tian, Qiong & Liu, Peng & Ong, Ghim Ping & Huang, Hai-Jun, 2021. "Morning commuting pattern and crowding pricing in a many-to-one public transit system with heterogeneous users," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    4. 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.
    5. Peer, Stefanie & Knockaert, Jasper & Verhoef, Erik T., 2016. "Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 314-333.
    6. Yap, Menno & Cats, Oded, 2021. "Taking the path less travelled: Valuation of denied boarding in crowded public transport systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 1-13.
    7. Márquez, Luis & Alfonso A, Julieth V. & Poveda, Juan C., 2019. "In-vehicle crowding: Integrating tangible attributes, attitudes, and perceptions in a choice context between BRT and metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 452-465.
    8. Zhang, Junlin & Yang, Hai & Lindsey, Robin & Li, Xinwei, 2020. "Modeling and managing congested transit service with heterogeneous users under monopoly," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 249-266.
    9. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.
    10. Lin, Joanne Yuh-Jye & Jenelius, Erik & Cebecauer, Matej & Rubensson, Isak & Chen, Cynthia, 2023. "The equity of public transport crowding exposure," Journal of Transport Geography, Elsevier, vol. 110(C).
    11. Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs & Daziano, Ricardo A., 2017. "Estimation of crowding discomfort in public transport: Results from Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 311-326.
    12. Peftitsi, Soumela & Jenelius, Erik & Cats, Oded, 2022. "Modeling the effect of real-time crowding information (RTCI) on passenger distribution in trains," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 354-368.
    13. Soza-Parra, Jaime & Raveau, Sebastián & Muñoz, Juan Carlos & Cats, Oded, 2019. "The underlying effect of public transport reliability on users’ satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 83-93.
    14. 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.
    15. 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.
    16. 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).
    17. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    18. Liu, Peng & Liu, Jielun & Ong, Ghim Ping & Tian, Qiong, 2020. "Flow pattern and optimal capacity in a bi-modal traffic corridor with heterogeneous users," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    19. Li, Hao & Gao, Kun & Tu, Huizhao, 2017. "Variations in mode-specific valuations of travel time reliability and in-vehicle crowding: Implications for demand estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 250-263.
    20. Junya Kumagai & Mihoko Wakamatsu & Shunsuke Managi, 2021. "Do commuters adapt to in-vehicle crowding on trains?," Transportation, Springer, vol. 48(5), pages 2357-2399, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:95:y:2017:i:c:p:105-125. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.