Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation
Han Ma, Yixin Ma, Jianhao Jiao, M. Usman Maqbool Bhutta, Mohammud Junaid Bocus, Lujia Wang, Ming Liu, Rui Fan · 2018
Lane detection is very important for self-driving vehicles. In recent years, computer stereo vision has been prevalently used to enhance the accuracy of the lane detection systems. This paper mainly presents a multiple lane detection algorithm developed based on optimised dense disparity map estimation, where the disparity information obtained at time tn is utilised to optimise the process of disparity estimation at time tn(n ≥ 0). This is achieved by estimating the road model at time tn and then controlling the search range for the disparity estimation at time tn+1. The lanes are then detected using our previously published algorithm, where the vanishing point information is used to model the lanes. The experimental results illustrate that the runtime of the disparity estimation is reduced by around 37% and the accuracy of the lane detection is about 99%.