This research focuses on two aspects of Intelligent Transportation System (ITS): Intelligent Traffic Light and Dynamic Route Guidance (DRG). The paper aims to make traffic light and route guidance to be smarter. In this paper, the authors apply Grey-Markov Model which combines Grey Model and Markov Model together to predict short-time traffic and then build Intelligent Traffic Light Model (ITLM). For purpose of realizing DRG, the authors improve ant colony optimization (ACO) by putting forward a new feedback pheromone and changing the probabilistic formula, which would make ACO feasible for solving the DRG in reality transportation. Simulations show that the model do have a better performance on short-time traffic predicting and improved ACO is suitable for DRG.


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    Titel :

    Intelligent Traffic Light Model Based on Grey-Markov Model and Improved Ant Colony Optimization for Dynamic Route Guidance


    Beteiligte:
    Zhao, Jiaxu (Autor:in) / Chen, Zhide (Autor:in) / Zeng, Yali (Autor:in)


    Erscheinungsdatum :

    01.11.2015


    Format / Umfang :

    467305 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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