Effects of pre-trip traffic information on intercity traveler's mode choice behaviors

Shou Ren Hu, Chun Ming Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Pre-trip traffic information is one of the crucial components that affect traveler's mode choice behaviors on intercity transportation corridors. Besides traveler's socioeconomic characteristics and transportation system's levels of service, there exists a specific relationship between pre-trip traffic information and user's internal decision process that jointly affect intercity traveler's mode choice behaviors. The present research employed latent variable models to investigate the effects and/or value of pre-trip traffic information on intercity users' mode choice behaviors. The empirical results indicated that certain latent variables inherent in travelers did influence users' intention in selecting a specific transportation mode. It was also found that by incorporating the significant latent variables into a discrete choice model to estimate intercity transportation systems' market shares, it is able to slightly improve model's performance.

Original languageEnglish
Title of host publicationIntelligent Transportation Society of America - 12th World Congress on Intelligent Transport Systems 2005
Pages1916-1925
Number of pages10
Publication statusPublished - 2009 Dec 1
Event12th World Congress on Intelligent Transport Systems 2005 - San Francisco, CA, United States
Duration: 2005 Nov 62005 Nov 10

Publication series

NameIntelligent Transportation Society of America - 12th World Congress on Intelligent Transport Systems 2005
Volume3

Other

Other12th World Congress on Intelligent Transport Systems 2005
CountryUnited States
CitySan Francisco, CA
Period05-11-0605-11-10

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Transportation
  • Automotive Engineering
  • Computer Networks and Communications
  • Artificial Intelligence
  • Computer Science Applications

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