IDEAS home Printed from https://ideas.repec.org/a/spr/pubtra/v11y2019i2d10.1007_s12469-019-00201-4.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12469-019-00201-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12469-019-00201-4?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. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nikita Moiseev & Alexey Mikhaylov & Igor Varyash & Abdul Saqib, 2020. "Investigating the relation of GDP per capita and corruption index," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(1), pages 780-794, September.
    2. Qiang, Shengjie & Huang, Qingxia, 2021. "Interactions between buses and cars in a two-lane mixed traffic system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).

    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. Fatemeh Enayatollahi & Ahmed Osman Idris & M. A. Amiri Atashgah, 2019. "Modelling bus bunching under variable transit demand using cellular automata," Public Transport, Springer, vol. 11(2), pages 269-298, August.
    2. Zhang, Shuyang & Lo, Hong K., 2018. "Two-way-looking self-equalizing headway control for bus operations," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 280-301.
    3. Varga, Balázs & Tettamanti, Tamás & Kulcsár, Balázs, 2019. "Energy-aware predictive control for electrified bus networks," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. Vismara, Luca & Chew, Lock Yue & Saw, Vee-Liem, 2021. "Optimal assignment of buses to bus stops in a loop by reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    5. 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.
    6. Weiya Chen & Hengpeng Zhang & Chunxiao Chen & Xiaofan Wei, 2021. "An Integrated Bus Holding and Speed Adjusting Strategy Considering Passenger’s Waiting Time Perceptions," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    7. Dai, Zhuang & Liu, Xiaoyue Cathy & Chen, Zhuo & Guo, Renyong & Ma, Xiaolei, 2019. "A predictive headway-based bus-holding strategy with dynamic control point selection: A cooperative game theory approach," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 29-51.
    8. Petit, Antoine & Lei, Chao & Ouyang, Yanfeng, 2019. "Multiline Bus Bunching Control via Vehicle Substitution," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 68-86.
    9. Liang, Shidong & He, Shengxue & Zhang, Hu & Ma, Minghui, 2021. "Optimal holding time calculation algorithm to improve the reliability of high frequency bus route considering the bus capacity constraint," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    10. Minyu Shen & Weihua Gu & Michael J. Cassidy & Yongjie Lin & Wei Ni, 2024. "A vicious cycle along busy bus corridors and how to abate it," Papers 2403.08230, arXiv.org.
    11. Bian, Bomin & Zhu, Ning & Meng, Qiang, 2023. "Real-time cruising speed design approach for multiline bus systems," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 1-24.
    12. Li, Shukai & Liu, Ronghui & Yang, Lixing & Gao, Ziyou, 2019. "Robust dynamic bus controls considering delay disturbances and passenger demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 88-109.
    13. Sánchez-Martínez, G.E. & Koutsopoulos, H.N. & Wilson, N.H.M., 2016. "Real-time holding control for high-frequency transit with dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 1-19.
    14. S. Sajikumar & D. Bijulal, 2022. "Zero bunching solution for a local public transport system with multiple-origins bus operation," Public Transport, Springer, vol. 14(3), pages 655-681, October.
    15. 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.
    16. Viktoriya Degeler & Léonie Heydenrijk-Ottens & Ding Luo & Niels Oort & Hans Lint, 2021. "Unsupervised approach towards analysing the public transport bunching swings formation phenomenon," Public Transport, Springer, vol. 13(3), pages 533-555, October.
    17. Zhou, Chang & Tian, Qiong & Wang, David Z.W., 2022. "A novel control strategy in mitigating bus bunching: Utilizing real-time information," Transport Policy, Elsevier, vol. 123(C), pages 1-13.
    18. Sirmatel, Isik Ilber & Geroliminis, Nikolas, 2018. "Mixed logical dynamical modeling and hybrid model predictive control of public transport operations," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 325-345.
    19. Dong Liu & Feng Xiao & Jian Luo & Fan Yang, 2023. "Deep Reinforcement Learning-Based Holding Control for Bus Bunching under Stochastic Travel Time and Demand," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    20. 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.

    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

    Statistics

    Access and download statistics

    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:spr:pubtra:v:11:y:2019:i:2:d:10.1007_s12469-019-00201-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.