The Method of Restricted Searching Area Optimal Route Guidance Based on Parallel Genetic Algorithm and Neural Network

Abstract

To work out route guidance in gigantic traffic network, the traffic information forecasting method based on Artificial Neural Network is studied in-depth and the time-varied road weight matrixes are constructed, which solve the problem of limitation in traditional and static road weight. The Parallel Genetic Algorithm (PGA) for optimal route choice is discussed in this paper and the corresponding genetic operator, mutation operator and the refresh way of the populations are also proposed. A method of Rectangle Restricted Searching Area (RRSA) which can reduce the searching area of PGA is presented. The problem of bad real-time and astringency of PGA existed in computing the optimal route in gigantic traffic network has also been solved using RRSA. To probe into the technology of the Route Guidance, a large number of experiments combined with the required analysis of the results have been carried on. It is indicated by simulation that the presented method of optimal route choice has achieved the accuracy, real-time and quick guidance in gigantic traffic network.