Robust lane detection and tracking for driving assistance systems

Abstract

This paper describes a novel approach of detecting lanes. The projective width of lanes can be computed precisely by a method of geometric projection to predict the relative position and features of lane markings. Besides, a camera's accurate tilt angle and the lane width can be acquired by dynamic calibration. Also, an algorithm named Lane Marking Extraction (LME) Finite State Machine (FSM) is proposed to capture the points with features of lane markings and use fuzzy reasoning to discriminate points of the lane markings. Some points are chosen as knots to supplement all of the points on the lane boundary with cubic B-spline interpolation, which reconstructs the area of lanes with a left and a right curve. The proposed approach uses prediction of a lane's projective width and the way of tracking to accelerate lane detections and to describe positions of lane markings on both sides effectively when one side is occluded.