交通系统的模糊控制及其神经网络实现

A FUZZY CONTROLLER OF TRAFFIC SYSTEMS AND ITS NEURAL NETWORK IMPLEMENTATION

  • 摘要: 本文根据城市交通系统的特点设计了单个路口信号灯的模糊控制器,研究了用神经网络实现模糊控制器的方法和过程,并对该控制器进行了仿真研究,本文所设计的控制方法适合于各种车流大小随机变化的单个路口,且决策过程迅速、合理,无需对车流进行预测,是一种实时单点控制方法,由于模糊控制器由神经网络实现,控制具有学习和联想功能,仿真结果说明了该方法的有效性.

     

    Abstract: In this paper, a neural network implemented fuzzy controller for single crossroad traffic signal control systems is presented, which is based on the summarization of the main characteristics of the traffic systems. The controller can cope with the fast changing of the arriving traffic flow and is suitable for all kinds of single crossroads and has a quite simple structure. The decision-making process is rapid as well as reasonable, with no need of any prediction of traffic flow. The simulation result is given, which verifies the effectiveness of this control method.

     

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