Automotive surface identification system based on modular neural network architecture

The development of automotive remote surface identification system is an important step in ensuring road safety. In this paper we shall discuss a novel approach which addresses the road surface classification process. This method is based on polarimetric radar and sonar data fusion and surface identification using artificial neural network. A modular artificial neural network, which is considered in the paper, allows an overall increase in classification accuracy in the presence of a large number of surface types and a large number of signal features. We shall discuss the techniques involved and present classification results that have been achieved using modular neural network.