摘要： 为保证自动驾驶的安全性和高效性,基于Hough变换与投票法找到道路图像的消隐点,以此建立动态感兴趣区域,根据白色与黄色车道线的颜色特性设计光照无关车道线检测算法,实现夜晚、隧道等复杂光照环境下的车道线区域检测。在此基础上,设计极角约束算法对候选车道线进行筛选,得到最终的有效车道线。实验结果表明,该算法在复杂光照环境下具有较好的检测效果,平均检测准确率高达93.5%。

关键词: 自动驾驶, 车道线检测, Hough变换, 动态感兴趣区域, 光照无关, 极角约束

Abstract: In order to ensure the safety and efficiency of automatic driving,the vanishing points of road images are found based on Hough transform and voting method,thereby establishing the Dynamic Region of Interest(DROI).Then the illumination invariant lane detection algorithm is designed according to the features of white and yellow lanes to realize the detection of lane area under various complicated illumination conditions such as night and tunnel.On this basis,a polar angle constraint algorithm is designed to screen the candidate lanes to get the final effective lane.Experimental results show that the algorithm has a good detection effect which can reach an average accurate detection rate of 93.5% under various complicated illumination conditions.

Key words: automated driving, lane detection, Hough transform, Dynamic Region of Interest(DROI), illumination invariant, polar angle constraint

中图分类号: 

• TP391.41