AN OVERVIEW OF ARTIFICIAL NEURAL NETWORKS APPLICATION IN TRANSPORTATION

An Artificial neural network (ANN) is a mathematical model that imitates biological neural network properties, and thus approximates operations of the human brain. Neural networks application helps to solved difficult problems that the human brain or other computational techniques can not. Neural networks are being widely used to real world problems; one of them is transportation systems. Nowadays the biggest problem for many cities is a poorly organized traffic management system, traffic flows rapidly increase in last years and cities are often not ready for this. ANN application can give a possibility to improve, optimise the transportation system. ANN's have already been different prediction, forecasting, classification, detection and estimation tasks. In the paper, successfully applied for different the neural networks based approaches (Multilayer, The Kohonen maps, Radial Basis function) for solving different , travel time and passenger demand forecasting, sign and moving transportation planning problems such as traffic object on the road recognition, incident detection are described.