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

作　　者：徐欣[1] 

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《计算机科学》2010年第2期250-252,共3页Computer Science

基　　金：科技部国家科技支撑计划项目(编号2008BADA6B01)资助

摘　　要：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.

关 键 词：交通控制 神经网络 关键车流 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP273[自动化与计算机技术—控制科学与工程]