Print Email Facebook Twitter An adaptive route choice model for integrated fixed and flexible transit systems Title An adaptive route choice model for integrated fixed and flexible transit systems Author Leffler, David (KTH Royal Institute of Technology) Burghout, Wilco (KTH Royal Institute of Technology) Cats, O. (TU Delft Transport and Planning; KTH Royal Institute of Technology) Jenelius, Erik (KTH Royal Institute of Technology) Date 2024 Abstract 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. Subject agent-based simulationflexible transitPublic transitroute choicetransit assignment To reference this document use: http://resolver.tudelft.nl/uuid:f06e8f3c-895d-4cf2-b4df-327543c98cb0 DOI https://doi.org/10.1080/21680566.2024.2303047 ISSN 2168-0566 Source Transportmetrica B: Transport Dynamics, 12 (1) Part of collection Institutional Repository Document type journal article Rights © 2024 David Leffler, Wilco Burghout, O. Cats, Erik Jenelius Files PDF An_adaptive_route_choice_ ... ystems.pdf 4.65 MB Close viewer /islandora/object/uuid:f06e8f3c-895d-4cf2-b4df-327543c98cb0/datastream/OBJ/view