城市单路口两级加权神经网络控制系统设计

Design of Hierarchical Weighted Neural Network Control System for City Traffic in Single Intersection

城市交通系统是一个非常复杂的非线性系统,很难建立精确的数学模型,而BP神经网络具有较强的自学习、自适应的特点,适合复杂的大系统。针对单交叉路口红绿灯控制问题,基于改进的BP神经网络算法,同时考虑关键车流和非关键车流信息,提出并设计了两级加权神经网络控制器来进行实时控制。仿真结果表明,本方法优于传统控制方法。

City traffic system is a very complicated non-linear system. It＇s very difficult to build precise mathematical model and BID neural network has advantage in self-study and self-adaption. In this paper, for the control problem in one intersection, based on improved BP neural network algorithm, considering key traffic flow and nonkey traffic flow, hiera- rchical weighted neural network controller was proposed and desiged. It＇s used to control traffic on time. The simula- tion results show that this control method is better than traditional methods.