Modeling the effects of population density on prospect theory-based travel mode-choice equilibrium

Ding Liu, Hing Keung William Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)


In conventional transportation planning models, it was always assumed that the population density is given and fixed in the study areas. Therefore, the effects of population density on travel choice have not been explicitly incorporated into these existing models for long-term transportation planning. Meanwhile, travel choice models in previous studies are usually developed by using discrete choice theories or user equilibrium principle. Thus, many significant characteristics of travelers’ behaviors, such as risk preference and learning process over time, cannot be considered in these conventional models. This article proposes a convex prospect theory-based model to investigate the effects of population density on the travelers’ mode-choice behavior under an advanced transportation information system (ATIS) in a multimodal transportation corridor. It is shown that population density is closely co-related to the modal split results and dependent on the performance of the railway mode in the study corridor. The park-and-ride mode may not be suitable for areas with high population density. This article also investigates the travelers’ reference points on the generalized travel costs by modes. A numerical example is given to illustrate the properties of the proposed model together with some insightful findings.
Original languageEnglish
Pages (from-to)379-392
Number of pages14
JournalJournal of Intelligent Transportation Systems: Technology, Planning, and Operations
Issue number4
Publication statusPublished - 1 Oct 2014


  • ATIS
  • Corridor
  • Multimodal
  • Population density
  • Prospect theory
  • Travel mode choice

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Automotive Engineering
  • Aerospace Engineering
  • Computer Science Applications
  • Applied Mathematics


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