A study on real time integrated lane detection and vehicle tracking method with side-mirror cameras

Vehicle detection in real-time from rear-side of a host vehicle is one of important problems in Lane Change Assistance. In this paper, we propose a vision system for real-time vehicle and lane detection and tracking using two cameras, which are equipped under the wing mirror both left and right side. From the input images, EDLines algorithm is used for line segment detection in real-time. According to the achieved data, lane detection is developed by analyzing angles of the line segments, and area between two lanes on the same side of vehicle is defined. In the vehicle detection, based on the brightness and darkness between vehicle and road, vehicle is detected in real-time using the simple algorithm. Finally, kalman filter is used in vehicle tracking for vehicle information such as distance or speed.