Lane Detection Based on Straight Line Model and K-Means Clustering

This paper presents an effective and robust algorithm to detect the lanes in highway. It uses Hough Transform to fit the lane line of top view of the road and extracts the most representative lane line in each category after clustering all the lines, which is then followed by a post-processing step. The results show that this algorithm can effectively reduce the disturbance of vehicles and guardrails to achieve 90% correct rate.