• DocumentCode
    3722492
  • Title

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

  • Author

    Jiaxu Zhao;Zhide Chen;Yali Zeng

  • Author_Institution
    Fujian Provincial Key Lab. of Network Security &
  • fYear
    2015
  • Firstpage
    204
  • Lastpage
    212
  • Abstract
    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.
  • Keywords
    "Vehicles","Predictive models","Computational modeling","Real-time systems","Mathematical model","Markov processes","Data models"
  • Publisher
    ieee
  • Conference_Titel
    Cyber Security and Cloud Computing (CSCloud), 2015 IEEE 2nd International Conference on
  • Type

    conf

  • DOI
    10.1109/CSCloud.2015.62
  • Filename
    7371482