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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    Title :

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


    Contributors:
    Zhao, Jiaxu (author) / Chen, Zhide (author) / Zeng, Yali (author)


    Publication date :

    2015-11-01


    Size :

    467305 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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