The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.


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    Title :

    Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities


    Contributors:

    Published in:

    Transport Reviews ; 36 , 4 ; 454-478


    Publication date :

    2016-07-03


    Size :

    25 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English