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.
Intelligent Traffic Light Model Based on Grey-Markov Model and Improved Ant Colony Optimization for Dynamic Route Guidance
01.11.2015
467305 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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