Integrated Vehicle and Lane Detection with Distance Estimation

In this paper, we propose an integrated system that combines vehicle detection, lane detection, and vehicle distance estimation in a collaborative manner. Adaptive search windows for vehicles provide constraints on the width between lanes. By exploiting the constraints, the search space for lane detection can be efficiently reduced. We employ local patch constraints for lane detection to improve the reliability of lane detection. Moreover, it is challenging to estimate the vehicle distance from images/videos captured form monocular camera in real time. In our approach, we utilize lane marker with the associated 3D constraint to estimate the camera pose and the distances to frontal vehicles. Experimental results on real videos show that the proposed system is robust and accurate in terms of vehicle and lane detection and vehicle distance estimation.