A study of freeway drivers’ demand for real-time traffic information along main freeways and alternative routes

A computer-aided survey was designed and conducted face-to-face with freeway drivers in Taiwan to gauge the demand for and reasonable pricing of customized real-time traffic information in the event of three different traffic conditions. Bivariate ordered probit models were estimated to investigate factors that significantly influence the demand for traffic information both for main freeways and secondary alternative routes. The results indicated that the demand for traffic information for non-recurring conditions was the strongest of the factors investigated. Basic information was the main type of information requested for normal and recurring conditions, whereas dynamic travel time prediction was the main type of information requested for non-recurring conditions. The estimation results from bivariate ordered probit models showed that by providing node-to-node information and encouraging a greater willingness to pay for information the demand for traffic information about main freeways and secondary alternative routes will increase. Finally, the significant and positive correlations of models imply that the greater the demand for traffic information about main freeways, the greater the demand for information about secondary alternative routes.

• Record URL:
  • https://doi.org/10.1016/j.trc.2013.02.011
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0968090X1300048X
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Jou, Rong-Chang
  • Chen, Ke-Hong
• Publication Date: 2013-6

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 62-72
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 31
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Advanced traveler information systems; Automobile drivers; Freeways; Needs assessment; Real time information; Route guidance; Surveys
• Uncontrolled Terms: Willingness to pay
• Geographic Terms: Taiwan
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01485229
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 28 2013 9:11AM