Artificial transportation systems (ATS) are an extension of traffic simulations that deal with transportation issues from the complex systems perspective in a systematic and synthetic way. A rule-based iterative ATS design process is presented in this paper, together with a prototype based on the multiagent platform-Swarm and the methods and results of computational experiments conducted on it. Both emergence-based observation and statistical analysis are used to evaluate those results. This paper demonstrates the ability of ATS to generate traffic phenomena from simple consensus rules and the possibility of designing a growing ATS with readily available multiagent tools.


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    Title :

    Growing Artificial Transportation Systems: A Rule-Based Iterative Design Process


    Contributors:
    Jinyuan Li, (author) / Shuming Tang, (author) / Xiqin Wang, (author) / Wei Duan, (author) / Fei-Yue Wang, (author)


    Publication date :

    2011-06-01


    Size :

    813428 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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