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Understanding the factors that influence the probability and time to streetcar bunching incidents

Author

Listed:
  • Paula Nguyen

    (University of Toronto)

  • Ehab Diab

    (University of Saskatchewan)

  • Amer Shalaby

    (University of Toronto)

Abstract

Bunching is a well-known operational problem for transit agencies and it has negative impacts on service quality and users’ perception. While there has been a substantial amount of literature about understanding the factors associated with bus bunching and strategies used to mitigate the effects of this problem, there has been little research on streetcar bunching. Although bus and streetcar systems share many similarities, one major difference between the two is that streetcars cannot overtake each other. This makes bunching in streetcar networks more critical to the reliability of the system and an important topic that requires more in-depth understanding. This research aims at understanding the factors that are associated with the likelihood of streetcar bunching and to investigate in greater detail the external and internal factors that relate to the time to the initial bunching incident from terminal. To achieve the first goal, the study uses a binary logistic regression model, while it uses an accelerated failure time model to address the second goal. The study utilizes automatic vehicle location system data acquired from the Toronto Transit Commission, the transit provider for the City of Toronto. The models’ results show that headway deviations at terminals are related to both an increase in the probability of bunching and an acceleration of the time to bunching. The discrepancy in vehicle types between two successive streetcars also has the same relationship as headway deviations at terminals. This study offers a better understanding of the factors that are associated with streetcar service bunching, which is an important component of transit service reliability.

Suggested Citation

  • Paula Nguyen & Ehab Diab & Amer Shalaby, 2019. "Understanding the factors that influence the probability and time to streetcar bunching incidents," Public Transport, Springer, vol. 11(2), pages 299-320, August.
    • Handle: RePEc:spr:pubtra:v:11:y:2019:i:2:d:10.1007_s12469-019-00201-4
    DOI: 10.1007/s12469-019-00201-4
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    References listed on IDEAS

    as
    1. David Verbich & Ehab Diab & Ahmed El-Geneidy, 2016. "Have they bunched yet? An exploratory study of the impacts of bus bunching on dwell and running times," Public Transport, Springer, vol. 8(2), pages 225-242, September.
    2. Xuan, Yiguang & Argote, Juan & Daganzo, Carlos F., 2011. "Dynamic bus holding strategies for schedule reliability: Optimal linear control and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1831-1845.
    3. Petit, Antoine & Ouyang, Yanfeng & Lei, Chao, 2018. "Dynamic bus substitution strategy for bunching intervention," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 1-16.
    4. Daganzo, Carlos F., 2009. "A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 913-921, December.
    5. Bartholdi, John J. & Eisenstein, Donald D., 2012. "A self-coördinating bus route to resist bus bunching," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 481-491.
    6. Andres, Matthias & Nair, Rahul, 2017. "A predictive-control framework to address bus bunching," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 123-148.
    7. Liang, Shidong & Zhao, Shuzhi & Lu, Chunxiu & Ma, Minghui, 2016. "A self-adaptive method to equalize headways: Numerical analysis and comparison," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 33-43.
    8. Daganzo, Carlos F. & Pilachowski, Josh, 2011. "Reducing bunching with bus-to-bus cooperation," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 267-277, January.
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    More about this item

    Keywords

    Streetcar; Bunching; Reliability; Accelerated failure time (AFT) model; Survival analysis;
    All these keywords.

    JEL classification:

    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General

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