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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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    1. Desjardins, Denise & Dionne, Georges & Pinquet, Jean, 2001. "Experience Rating Schemes for Fleets of Vehicles," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, pages 81-105.
    2. de Palma, André & Lindsey, Robin, 2001. "Optimal timetables for public transportation," Transportation Research Part B: Methodological, Elsevier, pages 789-813.
    3. Ceder, A. & Golany, B. & Tal, O., 2001. "Creating bus timetables with maximal synchronization," Transportation Research Part A: Policy and Practice, Elsevier, pages 913-928.
    4. Chen, Xumei & Yu, Lei & Zhang, Yushi & Guo, Jifu, 2009. "Analyzing urban bus service reliability at the stop, route, and network levels," Transportation Research Part A: Policy and Practice, Elsevier, pages 722-734.
    5. Strathman, James G. & Hopper, Janet R., 1993. "Empirical analysis of bus transit on-time performance," Transportation Research Part A: Policy and Practice, Elsevier, pages 93-100.
    6. Olsson, Nils O.E. & Haugland, Hans, 2004. "Influencing factors on train punctuality--results from some Norwegian studies," Transport Policy, Elsevier, pages 387-397.
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    Cited by:

    1. 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, pages 46-67.
    2. 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, pages 38-75.
    3. Shen, Yindong & Xu, Jia & Li, Jingpeng, 2016. "A probabilistic model for vehicle scheduling based on stochastic trip times," Transportation Research Part B: Methodological, Elsevier, pages 19-31.

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