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Quantification and control of disruption propagation in multi-level public transport networks
Delft University of Technology, NLD.
Delft University of Technology, NLD.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-8373-8398
Delft University of Technology, NLD.
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2022 (English)In: International Journal of Transportation Science and Technology, ISSN 2046-0430, E-ISSN 2046-0449, Vol. 11, no 1, p. 83-106Article in journal (Refereed) Published
Abstract [en]

Due to the multi-level nature of public transport networks, disruption impacts may spill-over beyond the primary effects occurring at the disrupted network level. During a public transport disruption, it is therefore important to quantify and control the disruption impacts for the total public transport network, instead of delimiting the analysis of their impacts to the public transport network level where this particular disruption occurs. We propose a modelling framework to quantify disruption impact propagation from the train network to the urban tram or bus network. This framework combines an optimisation-based train rescheduling model and a simulation-based dynamic public transport assignment model in an iterative procedure. The iterative process allows devising train schedules that take into account their impact on passenger flow re-distribution and related delays. Our study results in a framework which can improve public transport contingency plans on a strategic and tactical level in response to short- to medium-lasting public transport disruptions, by incorporating how the passenger impact of a train network disruption propagates to the urban network level. Furthermore, this framework allows for a more complete quantification of disruption costs, including their spilled-over impacts, retrospectively. We illustrate the successful implementation of our framework to a multi-level case study network in the Netherlands. © 2021 Tongji University and Tongji University Press

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 11, no 1, p. 83-106
Keywords [en]
Dynamic assignment, Optimisation, Public transport, Train rescheduling, Vulnerability analysis
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:bth-21418DOI: 10.1016/j.ijtst.2021.02.002ISI: 001045843700001Scopus ID: 2-s2.0-85105259516OAI: oai:DiVA.org:bth-21418DiVA, id: diva2:1556435
Part of project
TRANS-FORM - Smart transfers through unravelling urban form and travel flow dynamics, Swedish Research Council Formas
Funder
Swedish Research Council Formas, 942 - 2015-2034
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open access

Available from: 2021-05-21 Created: 2021-05-21 Last updated: 2024-06-28Bibliographically approved

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Törnquist Krasemann, Johanna

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CiteExportLink to record
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Citation style
  • apa
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Output format
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