An adaptive route choice model for integrated fixed and flexible transit systems
Document Type
Journal Article
Publication Date
2024
Subject Area
place - europe, place - urban, planning - integration, planning - methods, planning - service level, ridership - behaviour, ridership - demand, ridership - mode choice, ridership - modelling, technology - passenger information, technology - intelligent transport systems, operations - scheduling
Keywords
Public transit, flexible transit, agent-based simulation, transit assignment, route choice
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.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Leffler, D., Burghout, W., Cats, O., & Jenelius, E. (2024). An adaptive route choice model for integrated fixed and flexible transit systems. Transportmetrica B: Transport Dynamics, 12(1), 2303047.
