Citation

Jou RC, Chen KH. Transp. Res. C Emerg. Technol. 2013; 31: 62-72.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.trc.2013.02.011

PMID

unavailable

Abstract

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.