A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approa...A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.展开更多
A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and...A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.展开更多
A robust lane detection and tracking system based on monocular vision is presented in this paper. First, the lane detection algorithm can transform raw images into top view images by inverse perspective mapping （ IPM...A robust lane detection and tracking system based on monocular vision is presented in this paper. First, the lane detection algorithm can transform raw images into top view images by inverse perspective mapping （ IPM）, and detect both inner sides of the lane accurately from the top view im- ages. Then the system will turn to lane tracking procedures to extract the lane according to the infor- mation of last frame. If it fails to track the lane, lane detection will be triggered again until the true lane is found. In this system, 0-oriented Hough transform is applied to extract candidate lane mark- ers, and a geometrical analysis of the lane candidates is proposed to remove the outliers. Additional- ly, vanishing point and region of interest（ROI） dynamically planning are used to enhance the accura- cy and efficiency. The system was tested under various road conditions, and the result turned out to be robust and reliable.展开更多
考虑车道线的方向特性,提出一种应用方向可调滤波器的图像预处理方法。在对图像中的车道线方向特性进行分析的基础上,对图像进行分区处理,在每个区域内使用符合该区车道线方向的方向可调滤波器。在车道线初始检测阶段,利用边缘分布函数(...考虑车道线的方向特性,提出一种应用方向可调滤波器的图像预处理方法。在对图像中的车道线方向特性进行分析的基础上,对图像进行分区处理,在每个区域内使用符合该区车道线方向的方向可调滤波器。在车道线初始检测阶段,利用边缘分布函数(Edge distribution function,EDF)确定车道线方向;在车道线跟踪阶段,则把上一轮检测结果作为方向可调滤波器的方向角输入。对比分析表明,该方法能够更加有效地强化车道线信息,去除图像噪声。经过多种工况下的试验验证,应用方向可调滤波器的车道线识别方法能够稳定地对车道线进行识别,准确地提取车道线参数,并且算法实时性很高。展开更多
基金Project(90820302) supported by the National Natural Science Foundation of China
文摘A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.
基金Project(51175159)supported by the National Natural Science Foundation of ChinaProject(2013WK3024)supported by the Science andTechnology Planning Program of Hunan Province,ChinaProject(CX2013B146)supported by the Hunan Provincial InnovationFoundation for Postgraduate,China
文摘A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.
基金Supported by the National Natural Science Foundation of China(51005019)
文摘A robust lane detection and tracking system based on monocular vision is presented in this paper. First, the lane detection algorithm can transform raw images into top view images by inverse perspective mapping （ IPM）, and detect both inner sides of the lane accurately from the top view im- ages. Then the system will turn to lane tracking procedures to extract the lane according to the infor- mation of last frame. If it fails to track the lane, lane detection will be triggered again until the true lane is found. In this system, 0-oriented Hough transform is applied to extract candidate lane mark- ers, and a geometrical analysis of the lane candidates is proposed to remove the outliers. Additional- ly, vanishing point and region of interest（ROI） dynamically planning are used to enhance the accura- cy and efficiency. The system was tested under various road conditions, and the result turned out to be robust and reliable.
文摘考虑车道线的方向特性,提出一种应用方向可调滤波器的图像预处理方法。在对图像中的车道线方向特性进行分析的基础上,对图像进行分区处理,在每个区域内使用符合该区车道线方向的方向可调滤波器。在车道线初始检测阶段,利用边缘分布函数(Edge distribution function,EDF)确定车道线方向;在车道线跟踪阶段,则把上一轮检测结果作为方向可调滤波器的方向角输入。对比分析表明,该方法能够更加有效地强化车道线信息,去除图像噪声。经过多种工况下的试验验证,应用方向可调滤波器的车道线识别方法能够稳定地对车道线进行识别,准确地提取车道线参数,并且算法实时性很高。
