Restricted Searching Area Route Guidance Based on Neural Network and EA

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.