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Dynamic Control of Complex Transit Systems

Author

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  • Argote-Cabanero, Juan
  • Daganzo, Carlos F
  • Lynn, Jacob W

Abstract

This paper proposes a dynamic control method to overcome bunching and improve the regularity of fixed-route transit systems. The method uses a combination of dynamic holding and en-route driver guidance to achieve its objectives. It applies to systems with a mix of headway-based and schedule-based lines but it is evaluated for scheduled systems as this is the more challenging application. Improved schedule adherence is the goal. The method’s calculation complexity per piece of advice does not increase with system size. As a result, the method is scalable and can be used with large multiline systems, no matter how complex. When controled, each vehicle is mostly affected by exogenous disturbances (e.g. traffic) and very little by other vehicles. As a result, disruptions to a vehicle or group of vehicles caused by inattentive drivers or control equipment failures remain confined to the vehicles experiencing the problems. The control method effectively quarantines “disease”. The method is evaluated analytically and with simulations over a broad range of conditions, including schedules with zero slack. The method was also evaluated by observing the performance of a real world multi-line system that uses inexpensive on-board tablets to apply the control. The evaluation addresses driver compliance and equipment malfunction issues. It is found that the method is resilient and improves reliability considerably even under challenging conditions.

Suggested Citation

  • Argote-Cabanero, Juan & Daganzo, Carlos F & Lynn, Jacob W, 2015. "Dynamic Control of Complex Transit Systems," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6j16889k, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt6j16889k
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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

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    Cited by:

    1. Seyed Mohammad Hossein Moosavi & Amiruddin Ismail & Choon Wah Yuen, 2020. "Using simulation model as a tool for analyzing bus service reliability and implementing improvement strategies," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-26, May.
    2. Wu, Weitiao & Lin, Yue & Liu, Ronghui & Jin, Wenzhou, 2022. "The multi-depot electric vehicle scheduling problem with power grid characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 322-347.
    3. Berrebi, Simon J. & Crudden, Sean Óg & Watkins, Kari E., 2018. "Translating research to practice: Implementing real-time control on high-frequency transit routes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 213-226.
    4. van Lieshout, R.N. & Bouman, P.C. & van den Akker, M. & Huisman, D., 2020. "A Self-Organizing Policy for Vehicle Dispatching in Public Transit Systems with Multiple Lines," Econometric Institute Research Papers EI2020-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. 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.
    6. 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.
    7. Wu, Weitiao & Liu, Ronghui & Jin, Wenzhou, 2017. "Modelling bus bunching and holding control with vehicle overtaking and distributed passenger boarding behaviour," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 175-197.
    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. Gkiotsalitis, K. & Cats, O., 2021. "At-stop control measures in public transport: Literature review and research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    11. van Lieshout, Rolf N. & Bouman, Paul C. & van den Akker, Marjan & Huisman, Dennis, 2021. "A self-organizing policy for vehicle dispatching in public transit systems with multiple lines," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 46-64.
    12. Anderson, Paul & Daganzo, Carlos F., 2020. "Effect of transit signal priority on bus service reliability," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 2-14.

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    More about this item

    Keywords

    Engineering; transit reliability; real world operation; human factors; bus bunching; adaptive control; dynamic holding; multi-line control; resiliency;
    All these keywords.

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