Highlights • Develop a link-based mean-excess traffic equilibrium (L-METE) model.• Integrate the sub-additivity property of mean-excess travel time (METT).• Avoid normal route travel time distribution assumption in most route-based models.• L-METE is solvable by adapting existing algorithms for the conventional UE problem.• Avoid solving the nonadditive shortest path problem and storing/enumerating routes.

    Abstract Traffic equilibrium models under uncertainty characterize travelers’ route choice behaviors under travel time variability. In this paper, we develop a link-based mean-excess traffic equilibrium (L-METE) model by integrating the sub-additivity property and complete travel time variability characterization of mean-excess travel time (METT), and the computationally tractable additive route cost structure of the conventional user equilibrium (UE) problem. Compared to the majority of relevant models formulated in the route domain, the link-based modeling has two desirable features on modeling flexibility and algorithmic development. First, it avoids the normal route travel time distribution assumption (uniformly imposed for all routes) that inherits from the Central Limit Theorem in most route-based models, permitting the use of any suitable link travel time distributions from empirical studies. Second, the additive route cost structure makes the L-METE model solvable by readily adapting existing UE algorithms without the need of storing/enumerating routes while avoiding the computationally demanding nonadditive shortest path problem and route flow allocations in route-based models, which is a significant benefit for large-scale network applications under uncertainty.


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    Title :

    A link-based mean-excess traffic equilibrium model under uncertainty


    Contributors:
    Xu, Xiangdong (author) / Chen, Anthony (author) / Cheng, Lin (author) / Yang, Chao (author)


    Publication date :

    2016-10-31


    Size :

    23 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English