This study presents a distributed gradient-based approach to solve system optimal dynamic traffic assignment (SODTA) formulated based on the cell transmission model. The algorithm distributes SODTA into local sub-problems, who find optimal values for their decision variables within an intersection. Each sub-problem communicates with its immediate neighbors to reach a consensus on the values of common decision variables. A sub-problem receives proposed values for common decision variables from all adjacent sub-problems and incorporates them into its own offered values by weighted averaging and enforcing a gradient step to minimize its objective function. Then, the updated values are projected onto the feasible region of the sub-problems. The algorithm finds high quality solutions in all tested scenarios with a finite number of iterations. The algorithm is tested on a case study network under different demand levels and finds solutions with at most a 5% optimality gap.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Distributed Gradient Approach for System Optimal Dynamic Traffic Assignment


    Contributors:

    Published in:

    Publication date :

    2022-10-01


    Size :

    5093169 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    A System Optimal Traffic Assignment Model with Distributed Parameters

    Codina, E. / Barcelo, J. / Italian National Research Council; Progetto Finalizzato Transporti et al. | British Library Conference Proceedings | 1996


    Combinatorial Approach for Multiple-Destination User Optimal Dynamic Traffic Assignment

    Golani, H. / Waller, S. T. / Transportation Research Board | British Library Conference Proceedings | 2004


    Combinatorial Approach for Multiple-Destination User Optimal Dynamic Traffic Assignment

    Golani, Hina / Waller, S. Travis | Transportation Research Record | 2004