A novel approach to lane detection and tracking

In this paper, a new robust approach for camera based lane recognition is presented. The tracking filter and the detection interact such that the tracking filter is used to place a region of interest for a detection of lane segments in various distances, and each successful detection is used to update the lane geometry in the tracking filter. A novel and time efficient detection algorithm is used to detect the position and the slope of the lane segments. To be able to cope with sudden changes in the curvature, two interacting Extended Kalman filters are used to select the bandwidth for the filter. To our best knowledge this algorithm has not been applied to vision based lane tracking before. First results indicate that our approach is robust and real time capable with an average execution time of below 3 ms on a 3Ghz standard PC.