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Estimation of passenger waiting time using automatically collected transit data

Author

Listed:
  • Alexander Webb

    (University of Minnesota)

  • Pramesh Kumar

    (University of Minnesota)

  • Alireza Khani

    (University of Minnesota)

Abstract

Among the many ways to improve a transit system is a reduction in travel time as experienced by the passenger. Hence, passenger waiting times remain a topic of interest among transit planners. In this study, the effects of transit vehicle delays on passenger waiting time is investigated, as well as the effects of transfer status, boarding location, time of day, and rider travel frequency. The data used in this study were collected using automatic fare collection (AFC) and automatic vehicle location (AVL) technology. A trip chaining algorithm is used to infer the trajectory of each passenger, and as a result produce measures of passenger waiting time and vehicle delay. An analysis of an arterial Bus Rapid Transit (aBRT) line in Saint Paul, Minnesota reveals a waiting time model consistent with previous literature, a positive relationship between vehicle delay and passenger waiting time, and an insignificant relationship between transfer status and passenger waiting time. Finally, a simple model relating waiting time and vehicle delay is provided for the purpose of transit planning and waiting time estimation.

Suggested Citation

  • Alexander Webb & Pramesh Kumar & Alireza Khani, 2020. "Estimation of passenger waiting time using automatically collected transit data," Public Transport, Springer, vol. 12(2), pages 299-311, June.
    • Handle: RePEc:spr:pubtra:v:12:y:2020:i:2:d:10.1007_s12469-020-00229-x
    DOI: 10.1007/s12469-020-00229-x
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    References listed on IDEAS

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    1. Arnold Barnett, 1974. "On Controlling Randomness in Transit Operations," Transportation Science, INFORMS, vol. 8(2), pages 102-116, May.
    2. Huibo Gong & Xumei Chen & Lei Yu & Lijuan Wu, 2016. "An application-oriented model of passenger waiting time based on bus departure time intervals," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(4), pages 424-437, June.
    3. E. E. Osuna & G. F. Newell, 1972. "Control Strategies for an Idealized Public Transportation System," Transportation Science, INFORMS, vol. 6(1), pages 52-72, February.
    4. Delignette-Muller, Marie Laure & Dutang, Christophe, 2015. "fitdistrplus: An R Package for Fitting Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i04).
    5. Mohammad Reza Amin-Naseri & Vahid Baradaran, 2015. "Accurate Estimation of Average Waiting Time in Public Transportation Systems," Transportation Science, INFORMS, vol. 49(2), pages 213-222, May.
    6. J. K. Jolliffe & T. P. Hutchinson, 1975. "A Behavioural Explanation of the Association Between Bus and Passenger Arrivals at a Bus Stop," Transportation Science, INFORMS, vol. 9(3), pages 248-282, August.
    7. Marie Laure Delignette-Muller & Christophe Dutang, 2015. "fitdistrplus : An R Package for Fitting Distributions," Post-Print hal-01616147, HAL.
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    Cited by:

    1. Pramesh Kumar & Alireza Khani, 2021. "Adaptive Park-and-ride Choice on Time-dependent Stochastic Multimodal Transportation Network," Networks and Spatial Economics, Springer, vol. 21(4), pages 771-800, December.
    2. Zack Aemmer & Andisheh Ranjbari & Don MacKenzie, 2022. "Measurement and classification of transit delays using GTFS-RT data," Public Transport, Springer, vol. 14(2), pages 263-285, June.
    3. Liping Ge & Malek Sarhani & Stefan Voß & Lin Xie, 2021. "Review of Transit Data Sources: Potentials, Challenges and Complementarity," Sustainability, MDPI, vol. 13(20), pages 1-37, October.

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