A New Lane Line Segmentation and Detection Method based on Inverse Perspective Mapping

Abstract

Lane line detection plays an important role in vehicle autonomous driving, however non lane line markings and vehicle shadows seriously influence lane line detection results. In this paper, we propose a new lane line segmentation and detection algorithm based on inverse perspective mapping (IPM). Firstly, by using the restriction of the consistent lane line width after IPM, we segment the lane line and project the segmentation results back to the original coordinate system; then detect the right and left two lane lines by the gray scale weighted Hough transform method. Experimental results show that the proposed algorithm has strong robustness to non lane line markings and vehicle shadows, and the lane line can be accurately detected under the complex pavement conditions.