Traffic congestion is a menace in the society with serious economic implications. Pressure based routing systems are known to be effective in wireless sensor networks, however rarely applied to transportation systems due to the nature of interactions between vehicles. This paper aims to alleviate the traffic congestion by adapting the node pressure concept into the traffic management system. In particular, we propose a Multi-Agent System (MAS) with vehicle agents and infrastructure agents, which can collaborate to provide static and dynamic solutions for reducing the node pressure. Pertaining to the static solution, the infrastructure agents rely on a reinforcement learning method to calculate the optimal routes for vehicle agents. Pertaining to the dynamic solution, the infrastructure agents dynamically adjust and re-route vehicle agents based on a novel multi-unit combinatorial auctioning system proposed in this paper. Extensive experiments on realistic traffic simulation platform have proven our methods, especially the dynamic solution, to achieve significant improvement in the reduction of node pressure and travel-times for the vehicle agents in comparison to others.


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    Titel :

    Multiagent-based cooperative vehicle routing using node pressure and auctions


    Beteiligte:
    Seshadri, Madhavan (Autor:in) / Cao, Zhiguang (Autor:in) / Guo, Hongliang (Autor:in) / Zhang, Jie (Autor:in) / Fastenrath, Ulrich (Autor:in)


    Erscheinungsdatum :

    01.10.2017


    Format / Umfang :

    380830 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch