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Reducing passengers’ travel time by optimising stopping patterns in a large-scale network: A case-study in the Copenhagen Region

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  • Parbo, Jens
  • Nielsen, Otto A.
  • Prato, Carlo G.

Abstract

Optimising stopping patterns in railway schedules is a cost-effective way to reduce passengers’ generalised travel costs without increasing train operators’ costs. The challenge consists in striking a balance between an increase in waiting time for passengers at skipped stations and a decrease in travel time for through-going passengers, with possible consequent changes in the passenger demand and route choices. This study presents the formulation of the skip-stop problem as a bi-level optimisation problem where the lower level is a schedule-based transit assignment model that delivers passengers’ route choices to the skip-stop optimisation model at the upper level, and where the upper level in return provides an improved timetable to the lower level. A heuristic method for large-scale urban networks is presented to solve this extremely complex bi-level problem, where the skip-stop optimisation is a mixed-integer problem, whereas the route choice model is a non-linear non-continuous mapping of the timetable. The method was tested on the suburban railway network in the Greater Copenhagen Region (Denmark): the reduction in railway passengers’ in-vehicle travel time was 5.5%, the reduction in passengers’ generalised travel cost was 3.2% and, at the system level, the yearly consumer surplus amounted at 76.7 million DKK (about 10.3 million EUR or 12.7 million USD) when compared to the existing stopping patterns.

Suggested Citation

  • Parbo, Jens & Nielsen, Otto A. & Prato, Carlo G., 2018. "Reducing passengers’ travel time by optimising stopping patterns in a large-scale network: A case-study in the Copenhagen Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 197-212.
    • Handle: RePEc:eee:transa:v:113:y:2018:i:c:p:197-212
    DOI: 10.1016/j.tra.2018.04.012
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    References listed on IDEAS

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    1. Tétreault, Paul R. & El-Geneidy, Ahmed M., 2010. "Estimating bus run times for new limited-stop service using archived AVL and APC data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(6), pages 390-402, July.
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    7. Otto Nielsen & Rasmus Frederiksen, 2006. "Optimisation of timetable-based, stochastic transit assignment models based on MSA," Annals of Operations Research, Springer, vol. 144(1), pages 263-285, April.
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    Cited by:

    1. Emily Grisé & Ahmed El-Geneidy, 2020. "Assessing operation and customer perception characteristics of high frequency local and limited-stop bus service in Vancouver, Canada," Public Transport, Springer, vol. 12(3), pages 519-534, October.
    2. Guo, Xin & Wu, Jianjun & Sun, Huijun & Yang, Xin & Jin, Jian Gang & Wang, David Z.W., 2020. "Scheduling synchronization in urban rail transit networks: Trade-offs between transfer passenger and last train operation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 463-490.
    3. Jingfeng Yang & Hai Wang & Jiangang Jin, 2023. "Optimization of Station-Skip in a Cyclic Express Subway Service," Networks and Spatial Economics, Springer, vol. 23(2), pages 445-468, June.
    4. Gardner, Clara Brimnes & Nielsen, Sara Dorthea & Eltved, Morten & Rasmussen, Thomas Kjær & Nielsen, Otto Anker & Nielsen, Bo Friis, 2021. "Calculating conditional passenger travel time distributions in mixed schedule- and frequency-based public transport networks using Markov chains," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 1-17.
    5. Suman, Hemant & Larrain, Homero & Muñoz, Juan Carlos, 2021. "The impact of using a naïve approach in the limited-stop bus service design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 45-61.
    6. Ansari Esfeh, Mohammad & Saidi, Saeid & Wirasinghe, S.C. & Kattan, Lina, 2022. "Waiting time and headway modeling considering unreliability in transit service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 219-233.

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