A vision sensor system for intelligent vehicles

This paper proposes a vision sensor system to facilitate safer driving. The proposed system utilizes two low-cost compact Complementary Metal-Oxide Semiconductor (CMOS) cameras as vision sensors and an effective real-time detection algorithm to detect front vehicles and measure distances. Further, a custom-made binocular is used to capture pairs of images via a low-cost grabber card. This low-cost vision sensor is an asynchronous vision system because the left and right images have a slight time difference. However, the proposed detection algorithm, which comprises four modules - namely, image preprocessing, vehicle detection, detected vehicle tracking, and distance measurement - is unrestrained by the limitations of the epipolar constraints for synchronous vision systems, and also enables the system to overcome the asynchronous detection problem affecting conventional low-cost vision systems. The results of long-term performance tests conducted on highways and urban and country roads confirm that the proposed system can successfully detect the distance of the front vehicle with detection rates of up to 99%, and detect the distances of front vehicles under various weather and illumination conditions with detection rates of up to 93%.