Abstract
Considerable public and private resources are devoted to the collection and dissemination of real‐time traffic information in the Chicago area. Such information is intended to help individuals make more informed travel decisions, yet its effect on behavior remains largely unexplored. This study evaluates the effect of traffic information on travelers' route and departure time changes and provides a stronger basis for developing advanced information systems. Downtown Chicago automobile commuters were surveyed during the AM peak period. The results indicate that a majority of the respondents access, use and respond to information. For example, individuals use travel information to reduce their anxiety—even if they do not change travel decisions; this indicates that information may have “intrinsic” value. That is, simply knowing traffic conditions is valued by travelers. More than 60% of the respondents had used traffic information to modify their travel decisions. Multivariate analysis using the ordered probit model showed that individuals were more likely to use traffic reports for their route changes if they perceived traffic reports to be accurate and timely, and frequently listened to traffic reports. Respondents were more likely to change their departure times if they perceived traffic reports to be accurate and relevant, and frequently listened to traffic reports. The implication for Advanced Traveler Information Systems are that they may be designed to support both enroute and pre‐trip decisions. ATIS performance, measured in terms of accuracy, relevance and timeliness would be critical in the success of such systems. Further, near‐term prediction of traffic conditions on congested and unreliable routes (where conditions change rapidly) and incident durations is desirable.
Original language | English (US) |
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Pages (from-to) | 193-212 |
Number of pages | 20 |
Journal | Journal of Advanced Transportation |
Volume | 29 |
Issue number | 2 |
DOIs | |
State | Published - 1995 |
ASJC Scopus subject areas
- Automotive Engineering
- Economics and Econometrics
- Mechanical Engineering
- Computer Science Applications
- Strategy and Management