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

Jens Parbo, Otto Anker Nielsen, Carlo Giacomo Prato*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    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.
    Original languageEnglish
    JournalTransportation Research. Part A: Policy & Practice
    Volume113
    Pages (from-to)197-212
    Number of pages16
    ISSN0965-8564
    DOIs
    Publication statusPublished - 2018

    Keywords

    • Large-scale networks
    • Public transport optimisation
    • Public transport passengers’ behaviour
    • Railway timetabling
    • Stopping patterns

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