摘要
车道线检测是自动驾驶汽车或高级驾驶辅助系统的重要组成部分,利用安装在车辆前方的单目相机以实时成像的方式获取车辆在当前车道的横向偏移,从而为车辆的车道保持、超车换道等横向控制策略提供参考。本文提出了一种基于双灭点估计的实时、稳健的车道检测方法。首先利用尺度自适应的局部对称算子对车道线点特征进行提取;其次对左右车道线分别估计灭点,以灭点为导向,构建特征点的统计直方图;然后选择穿过大多数特征点的直线且通过特征点和所选线之间的重叠度对灭点进行估计更新,重复上一步骤以获得稳定的灭点;最后基于稳定的灭点验证并选择最佳的车道线。本文在公共数据集对提出的方法进行了测试,试验结果表明,本文方法在满足实时性的前提下,能有效提高算法整体的稳健性。
In automatic vehicles or advanced driving assistance systems,lane detection provides a way to guide the vehicle to drive along its own lane.An efficient lane detection method is proposed in this paper.Firstly,the lane features are extracted,and the lines are generated from vanishing points to image bottom.Then the lines crossing most features are selected and vanishing points are updated by the overlap between features and selected lines.Last step will be repeated until stable vanishing points are obtained.The last selected lines are most likely to be lane lines.Finally,validate and select the best lane lines.The proposed method has been tested on a public dataset.The experimental results show that the method can improve robustness under real-time automated driving.
作者
陈世增
李必军
周继苗
CHEN Shizeng;LI Bijun;ZHOU Jimiao(State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;Engineering Research Center of Spatio-Temporal Data Smart Acquisition and Application,Ministry of Education,Wuhan University,Wuhan 430079,China)
出处
《测绘通报》
CSCD
北大核心
2020年第1期16-20,共5页
Bulletin of Surveying and Mapping
基金
国家自然科学基金(41671441)
国家自然科学基金汽车产业创新发展联合基金(U1764262).
关键词
车道线检测
直方图
双灭点估计
重叠度
自动驾驶
lane detection
histogram
double vanishing points estimation
overlap
automated driving
