道路交叉口信号的模糊神经网络控制

A Traffic Signal Control Method for Isolated Intersection Applying Fuzzy Neural Network

应用模糊神经网络对交通系统进行控制是一种新的尝试 ,它可以充分发挥模糊逻辑和神经网络的优势 ,实现更为有效的控制。提出了一种基于模糊神经网络的道路交叉口交通信号控制方法 ,根据两相位的关键车流信息来决定绿灯延长时间 ,形成控制策略。仿真结果表明 ,与传统的定时控制方法相比 ,所提出的神经网络控制方法在车辆平均延误时间和排队长度方面都有较大改进 ,该方法有效。

It is a new attempt to use fuzzy neural network (FNN) as a traffic controller. The FNN traffic controller can work more effectively as it gives full play to both fuzzy logic system and neural network. A traffic control method applying FNN is proposed for isolated intersection in this paper. According to this method, the detected main data of vehicle flow in each direction is used to determine the control strategy. Compared with the ordinary traffic control system, the FNN control system is proved to be useful and effective by simulation results. It can improve the average delay of vehicles and the queue length.