A method of lane detection and tracking for expressway based on RANSAC

Abstract

Lane mark detection and tracking is essential for advanced driver assistance systems. We propose a computationally efficient lane mark detection and tracking method for expressway that can robustly and accurately detect lane marks in an image. A small size detection window scanner moving in the region of interest to determine whether there is a lane mark at the current position. This method can improve the detection accuracy and noise immunity. According to the correlations between video frames, we locate lane mark positions fast in current frame. We use an improved RANSAC method to fit the detected lane marks to straight lines. The proposed method is proved to be efficient through experiments for various complex environments.