Passenger Advice and Rolling Stock Rescheduling Under Uncertainty for Disruption Management

Evelien van der Hurk*, Leo Kroon, Gábor Maróti

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Operators and passengers need to adjust their plans in cases of large-scale disruptions in railway networks. Where most previous research has focused on the operators, this paper studies the combined support of both in a system where passengers have free route choice. In cases of disruption, passengers receive route advice, which they are not required to follow: passengers’ route choice depends on the route advice and the timetable information available to them. Simultaneous to providing advice, rolling stock is rescheduled to accommodate the anticipated passenger demand. The duration of the disruption is uncertain, and passenger flows arise from a complex interaction between
    the passengers’ route choices and the seat capacity allocated to the trains. We present an optimization-based algorithm that aims to minimize passenger inconvenience through
    provision of route advice and rolling stock rescheduling, where the advice optimization and rolling stock rescheduling modules are supported by a passenger simulation model.
    The algorithm aims to include and evaluate solutions under realistic passenger behavior assumptions. Our computational tests on realistic instances of Netherlands Railways
    indicate that the addition of the travel advice effectively improves the service quality to the passengers more than only rescheduling rolling stock, even when not all passengers
    follow the advice.
    Original languageEnglish
    JournalTransportation Science
    Issue number6
    Pages (from-to)1391-1411
    Publication statusPublished - 2018


    • Combinatorial optimization
    • Disruption management
    • Uncertainty
    • Public transport
    • Rolling stock rescheduling
    • Passenger advice


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