A Vision-Based Lane Detection and Tracking Algorithm
Жипенг Ли · Journal of Tongji University · 2010
This paper presents a novel lane detection and tracking algorithm for automatic drive system.The algorithm utilizes the generalized curve lane parameter model,which can describe both straight and curved lanes.The most prominent contribution of the detection algorithm lies in that:both the adaptive random Hough transformation (ARHT) algorithm and the tabu search algorithm are used to calculate the different parameters in the lane model according to different demands of accuracy for different parameters.Furthermore,a multi-resolution strategy is proposed to reduce the time-consumption of the whole system.At last,this paper also presents a tracking algorithm based on the particle filter to improve the stability of the whole system.Extensive experiments in variable occasions are implemented to prove the approach to be both robust and fast,besides,the algorithms can extract the lanes accurately even under unsatisfactory illumination situations.