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Timetable-based operation in urban transport: Run-time optimisation and improvements in the operating process

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  • Salicrú, M.
  • Fleurent, C.
  • Armengol, J.M.

Abstract

Urban public transit provides an efficient means of mobility and helps support social development and environmental preservation. To avoid loss of ridership, transit authorities have focussed on improving the punctuality of routes that operate using timetables. This paper presents a new approach to generating run-time values that is based on analytical development and micro simulations. The work utilizes previous research (described herein) and the experience acquired by Transports Metropolitans de Barcelona (TMB) in operating bus routes based on timetables. Using a sample of historical data, the method used for generating run-time values consists of the following steps: purging and screening atypical trips, based on the consideration of confidence intervals for median trips; segmenting the day into time bands based on the introduction of a new hierarchical classification algorithm; creating initial run-time values based on criteria derived from statistical analysis; adjusting and validating initial run-time values using micro simulations; and evaluating incident-recovery times at the end of trips in order to guarantee the punctual departure of the next trip in the vehicle schedule. To favour service improvement, we also introduced certain indicators that can identify the root causes of non-compliance. As a final step, in order to ensure the applicability and use of the model, we promoted the development of our model within the framework of the HASTUS(TM) software solution.

Suggested Citation

  • Salicrú, M. & Fleurent, C. & Armengol, J.M., 2011. "Timetable-based operation in urban transport: Run-time optimisation and improvements in the operating process," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 721-740, October.
    • Handle: RePEc:eee:transa:v:45:y:2011:i:8:p:721-740
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    References listed on IDEAS

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    Cited by:

    1. Yanan Zhang & Zhaopeng Meng & Yan Zheng & Anca Ralescu, 2019. "Schedule optimization under fuzzy constraints of vehicle capacity," Fuzzy Optimization and Decision Making, Springer, vol. 18(2), pages 131-150, June.
    2. Guo, Xin & Sun, Huijun & Wu, Jianjun & Jin, Jiangang & Zhou, Jin & Gao, Ziyou, 2017. "Multiperiod-based timetable optimization for metro transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 46-67.
    3. Xuesong Feng & Hanxiao Zhang & Yong Ding & Zhili Liu & Hongqin Peng & Bin Xu, 2013. "A Review Study on Traction Energy Saving of Rail Transport," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-9, September.
    4. Ibarra-Rojas, O.J. & Delgado, F. & Giesen, R. & Muñoz, J.C., 2015. "Planning, operation, and control of bus transport systems: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 38-75.
    5. Shen, Yindong & Xu, Jia & Li, Jingpeng, 2016. "A probabilistic model for vehicle scheduling based on stochastic trip times," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 19-31.

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