This study focuses on updating time-varying demand matrices by using real observation counts from advanced traffic management surveillance systems. A machine-learning technique using advanced evolutionary algorithms (EAs) is developed instead of the more conventional approaches in the literature. This EA-based demand estimation framework is implemented into a model called the Dynamic Origin–Destination (O-D) Estimator (DynODE). The potential of EAs in the dynamic O-D estimation problem lies in their powerful global search and optimization capabilities. DynODE is integrated with an existing dynamic traffic assignment platform (e.g., DYNASMART-P). The EA-based methods in this study are further augmented with EA parallelization to improve the quality and efficiency of the solution. DynODE mainly addresses offline O-D estimation problems. However, online O-D estimation can be achieved with the parallel version of DynODE with sufficient multiprocessing and parallel computing. The developed approach is rigorously evaluated on a medium-sized real network to assess the effects of various parallel structures. For all experiments, savings in computation resources as well as enhancement in the quality of solution were realized.


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    Titel :

    Noniterative Approach to Dynamic Traffic Origin–Destination Estimation with Parallel Evolutionary Algorithms


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Kattan, Lina (Autor:in) / Abdulhai, Baher (Autor:in)


    Erscheinungsdatum :

    01.01.2006




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Noniterative Approach to Dynamic Traffic Origin-Destination Estimation with Parallel Evolutionary Algorithms

    Kattan, L. / Abdulhai, B. / National Research Council (U.S.) | British Library Conference Proceedings | 2006





    Estimation of origin-destination flows for dynamic traffic assignment

    Brandriss, Josef Joshua, 1977- | DSpace@MIT | 2001

    Freier Zugriff