Automatic vehicle classification system with range sensors

Traffic management systems use inductive loop detectors and more recently video cameras to detect vehicles. Loop detectors are expensive to maintain and video-based systems are sensitive to environmental conditions and do not perform well in vehicle classification. Cameras based upon range sensors are not sensitive to lighting and may be less sensitive to other environmental conditions. In addition, range imagery should provide data to form a good basis for vehicle classification applications. In this paper, we describe methods for processing range imagery and performing vehicle detection and classification. A vehicle classification rate of over 92% accuracy was obtained in classifying vehicles into different vehicle classes.