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Optimal allocation of vehicles to bus routes using automatically collected data and simulation modelling

Author

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  • Sánchez-Martínez, Gabriel E.
  • Koutsopoulos, Haris N.
  • Wilson, Nigel H.M.

Abstract

Monitoring the service quality of high-frequency bus transit is important both to agencies running their own operations and those contracting out, where performance measures can be used to assess contract penalties or bonuses. The availability of automatically collected vehicle movement and demand data enables detecting changes in running times and demand, which may present opportunities to improve service quality and fleet utilization. This research develops a framework to maximize service performance in a set of high-frequency bus routes, given their planned headways and a total fleet size constraint. Using automatically collected data and simulation modelling to evaluate the performance of each route with varying fleet sizes, a greedy algorithm adjusts allocation toward optimality. A simplified case study involving morning peak service on nine bus routes in Boston demonstrates the feasibility and potential benefits of the approach. A potential application is automated detection of routes operating with insufficient or excessive resources.

Suggested Citation

  • Sánchez-Martínez, Gabriel E. & Koutsopoulos, Haris N. & Wilson, Nigel H.M., 2016. "Optimal allocation of vehicles to bus routes using automatically collected data and simulation modelling," Research in Transportation Economics, Elsevier, vol. 59(C), pages 268-276.
    • Handle: RePEc:eee:retrec:v:59:y:2016:i:c:p:268-276
    DOI: 10.1016/j.retrec.2016.06.003
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    References listed on IDEAS

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    1. Han, Anthony F. & Wilson, Nigel H. M., 1982. "The allocation of buses in heavily utilized networks with overlapping routes," Transportation Research Part B: Methodological, Elsevier, vol. 16(3), pages 221-232, June.
    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, vol. 77(C), pages 38-75.
    3. Martínez, Héctor & Mauttone, Antonio & Urquhart, María E., 2014. "Frequency optimization in public transportation systems: Formulation and metaheuristic approach," European Journal of Operational Research, Elsevier, vol. 236(1), pages 27-36.
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    Cited by:

    1. Seyedmostafa Zahedi & Haris N. Koutsopoulos & Zhenliang Ma, 2025. "Dynamic interlining in bus operations," Transportation, Springer, vol. 52(3), pages 827-850, June.
    2. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2020. "A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies," Applied Energy, Elsevier, vol. 261(C).

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