Real-Time Detection and Tracking of Vehicle Base Fronts for Measuring Traffic Counts and Speeds on Highways

Abstract

A real-time system is presented for automatically monitoring a highway when the camera is relatively low to the ground and on the side of the road. In such a case, occlusion and the perspective effects due to the heights of the vehicles cannot be ignored. The system presented in this paper is based on a novel technique of detecting and tracking the base fronts of vehicles. Compared with the authors’ previous approach, the proposed technique involves a simplified problem formulation, operates in real time, and requires only a small number of parameters to calibrate. Experimental results of a camera mounted at a height of 26 ft and a lateral distance of 12 ft from the edge of the pavement reveal accuracy as high as 98% with few false detections. The system can collect a variety of traffic data, including volume, time–mean speed and space–mean speed, density, vehicle classification, and lane change activities. By handling perspective effects and vehicle occlusions, the system overcomes some of the limitations of commercially available machine vision-based traffic monitoring systems that are used in many intelligent transportation systems applications.