A bounded path size route choice model excluding unrealistic routes: Formulation and estimation from a large-scale GPS study

Lawrence Christopher Duncan*, David Paul Watling, Richard Dominic Connors, Thomas Kjær Rasmussen, Otto Anker Nielsen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

This paper develops a new route choice modelling framework that deals with both route correlations and unrealistic routes in a consistent and robust way. To do this, we explore the integration of a correlation-based Path Size Logit model with the Bounded Choice Model (BCM) (Watling et al. 2018. “Stochastic User Equilibrium with a Bounded Choice Model.” Transportation Research Part B: Methodological 114: 254–280). We find, however, that the natural integration of these models leads to behavioural inconsistencies and/or undesirable mathematical properties. Solving these challenges, we derive a mathematically well-defined Bounded Path Size (BPS) model form that utilises a consistent criterion for assigning zero choice probabilities to unrealistic routes while eliminating their path size contributions. A closed-form and fixed-point BPS model are consequently formulated. Subsequently, we consider parameter estimation in a simulation study and on a real-life large-scale network using GPS data, where computational feasibility is demonstrated. Estimation results show the potential of the BPS models to give improved fit relative to non-bounded versions (and BCM).
Original languageEnglish
JournalTransportmetrica A: Transport Science
Pages (from-to)1-59
Number of pages59
ISSN1812-8602
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Bounded choice model
  • Path size logit
  • Route choice
  • Parameter estimation
  • Unrealistic routes

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