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An adaptive route choice model for integrated fixed and flexible transit systems
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-4556-4382
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0003-1514-6777
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-4506-0459
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-4106-3126
2024 (English)In: Transportmetrica B: Transport Dynamics, ISSN 2168-0566, Vol. 12, no 1Article in journal (Refereed) Published
Abstract [en]

Over the past decade, there has been a surge of interest in the application of agent-based simulation models to evaluate flexible transit solutions characterized by different degrees of short-term flexibility in routing and scheduling. A central modelling decision in the development is how one chooses to represent the mode- and route-choices of travellers. The real-time adaptive behaviour of travellers is important to model in the presence of a flexible transit service, where the routing and scheduling of vehicles is highly dependent on supply-demand dynamics at a near real-time temporal resolution. We propose a utility-based transit route-choice model with representation of within-day adaptive travel behaviour and between-day learning where station-based fixed-transit, flexible-transit, and active-mode alternatives may be dynamically combined in a single path. To enable experimentation, this route-choice model is implemented within an agent-based dynamic public transit simulation framework. We first explore model properties in a choice between fixed- and flexible-transit modes for a toy network. The adaptive route choice framework is then applied to a case study based on a real-life branched transit service in Stockholm, Sweden. This case study illustrates level-of-service trade-offs, in terms of waiting times and in-vehicle times, between passenger groups and analyzes traveller mode choices within a mixed fixed- and flexible transit system. Results show that the proposed framework is capable of capturing dynamic route choices in mixed flexible and fixed transit systems and that the day-to-day learning model leads to stable fixed-flexible mode choices.

Place, publisher, year, edition, pages
Informa UK Limited , 2024. Vol. 12, no 1
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-343550DOI: 10.1080/21680566.2024.2303047ISI: 001148712800001Scopus ID: 2-s2.0-85183167170OAI: oai:DiVA.org:kth-343550DiVA, id: diva2:1838590
Funder
EU, European Research Council, 804469Swedish Transport Administration, RV 2019/27044
Note

QC 20240219

Available from: 2024-02-16 Created: 2024-02-16 Last updated: 2024-02-19Bibliographically approved

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Leffler, DavidBurghout, WilcoCats, OdedJenelius, Erik

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