Restricted Searching Area Route Guidance Based on Neural Network and EA

摘要：

The traffic information forecasting method for route guidance in large traffic network, based on artificial neural network is studied and the time-varied road weight matrixes is constructed, in order to solve the problem of low forecasting rate in traditional and static road weight. An Evolution algorithm (EA) for optimal route choice is presented. The corresponding genetic operator, mutation operator and the refresh way for population are proposed. A Rectangle Restricted Searching Area (RRSA) method which can reduce the searching area of EA is presented. The problem of bad real-time and astringency of EA for optimal route computing in large traffic network is solved using RRSA. Simulation results have shown that good accuracy and real-time characteristics are got for route guidance in large traffic network.

关键词： Route guidance Neural network Rectangle restricted searching area Evolution algorithm1

作者: Zhonghua Han Chengdong Wu Bin Ma Jiejia Li Ke Xu

作者单位: Faculty of Information and Control Engineering Shenyang, Jianzhu University Shenyang, Liaoning, P.R.China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）