Title

Modeling drivers' diversion from normal routes under ATIS using generalized estimating equations and binomial probit link function

Authors

Authors

M. Abdel-Aty;M. F. Abdalla

Comments

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Abbreviated Journal Title

Transportation

Keywords

ATIS; GEE; normal route; repeated observations; travel simulator; LONGITUDINAL DATA; LINEAR-MODELS; CHOICE; Engineering, Civil; Transportation; Transportation Science & Technology

Abstract

Advanced Traveler Information Systems (ATIS) provide travelers with real time traffic information to optimize their travel choices. The objective of this paper is to model drivers' diversion from their normal routes in the provision of ATIS. Five different scenarios of traffic information are used. Generalized Estimating Equations ( GEE) framework with repeated observations and binomial probit link function is introduced and implemented. GEE with four different correlation structures including the independent case are developed and compared with each other and with regular Maximum Likelihood Estimation (MLE). A travel simulator was used. Sixty-five subjects have traveled 10 simulated trial days each on a 40-link realistic network with real historical congestion levels. The results showed that providing traffic information increases the probability of drivers' diversion from their normal routes. Adding advice to the pre-trip and/or en-route information encourages drivers to divert. Providing en-route in addition to the pre-trip information with or without advice increases the diversion probability. High travel time on the normal route and less travel time on the diverted route increase the probability of diversion. High-educated drivers are less likely to divert. Expressway users are more likely to divert from their normal routes under ATIS. Drivers' familiarity with the device that provides the information and high number of traffic signals on the normal route increase the diversion probability.

Journal Title

Transportation

Volume

31

Issue/Number

3

Publication Date

1-1-2004

Document Type

Article

Language

English

First Page

327

Last Page

348

WOS Identifier

WOS:000221056800004

ISSN

0049-4488

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