Modeling repeated multinomial route choices under advanced traveler information system - Generalized estimating equations with polytomous logit function

Authors

    Authors

    M. Abdel-Aty; M. F. Abdalla;Trb

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Keywords

    LONGITUDINAL DATA; DECISIONS; BEHAVIOR; Engineering, Civil; Operations Research & Management Science; Transportation Science & Technology

    Abstract

    Correlated multinomial route choice data were modeled under an advanced traveler information system (ATIS). A travel simulator was used as a dynamic data collection tool. The simulator uses realistic network and real historical traffic volumes. It provides five levels of ATIS and accounts for types of delay. A 25-node and 40-link network was used. Sixty-three qualified subjects performed a total of 539 trial days. Forty-four distinct routes were chosen. The multinomial generalized estimating equation (MGEE) methodology was used with a generalized polytomous function and an exchangeable correlation structure. MGEEs account for the serial correlation between repeated choices made by the same subject as well as the correlation due to the overlapping between alternatives. The modeling results show that drivers can identify and follow the shortest path when they are provided with advice-free traffic information on all the network links. In addition, it is shown that the odds of choosing a certain shortest-path route, whether the drivers are advised or not, vary from route to route, depending on the characteristics of the route itself. It was proved that the proposed model could account for a correlation in the multinomial repeated route choices with simple computational effort, even for a large number of alternatives.

    Journal Title

    Transportation Network Modeling 2004

    Issue/Number

    1882

    Publication Date

    1-1-2004

    Document Type

    Article

    Language

    English

    First Page

    61

    Last Page

    69

    WOS Identifier

    WOS:000227334100008

    ISSN

    0361-1981; 0-309-09475-5

    Share

    COinS