Travel Time Prediction Algorithms Based on RBF Neural Networks

Travel time prediction is one of main content in Intelligent Transportation System (ITS), accurate travel time prediction also is crucial application in the route guidance and advanced traveler information systems. In this paper, travel tine prediction algorithm based on RBF neural networks (RBFNN) is proposed, neural networks input is currently traveling time series data of each road segment. A gradient descend learning algorithm with a momentum factor in this network model is introduced to decide the positions of RBF centers in hidden layer, and output layer weight. Real road experiment results have shown that the proposed travel time prediction algorithm is feasible. Comparing with traditional method, the prediction error, both relative mean errors and root-mean-squared errors of travel times, is reduced significantly.