In this study, an experiment to establish a model for human-environment social systems, a multi-agent simulation model to deal with urban traffic congestion problems involving automobiles embedded with several strategies of car navigation systems (CNS), is presented. A shortest time route with route information sharing strategy (ST-RIS) is believed to be one of the solutions for a novel CNS based on bilateral information shared among automobile agents. The authors assume several strategies including ST-RIS for agents, which are defined differently in terms of their information-handling process. The question of which strategy is most appropriate for solving urban traffic congestion can be seen as a social dilemma, because social holistic utility may conflict with an agent's individual utility. The presented model shows that this social dilemma can be observed as a typical chicken-type dilemma, or as a typical minority game, where an agent who has adopted a minority strategy can earn more utility compared to when other strategies are used. Consequently, the model has illustrated that shortest time route with partial route information sharing strategy (ST-pRIS), which is an advanced strategic form of ST-RIS in which only partial information is shared among agents, has moderate potential to be diffused in a society from the viewpoint of the evolutionary game theory.


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    Title :

    Social diffusive impact analysis based on evolutionary computations for a novel car navigation system sharing individual information in urban traffic systems


    Additional title:

    Analyse sozialer Auswirkungen auf die evolutionären Berechnungen eines neuartigen Fahrzeugnavigationssystems mit Mitteilung individueller Informationen in einem städtischen Verkehrssystem


    Contributors:

    Published in:

    The Journal of Navigation ; 64 , 4 ; 711-725


    Publication date :

    2011


    Size :

    15 Seiten, 9 Bilder, 3 Tabellen, 27 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English