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首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >A Novel Strategy for Road Lane Detection and Tracking Based on a Vehicle’s Forward Monocular Camera
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A Novel Strategy for Road Lane Detection and Tracking Based on a Vehicle’s Forward Monocular Camera

机译：基于车辆前向单目摄像头的车道检测和跟踪新策略

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摘要

Modern road vehicles are employing features of driver assistance systems (DAS) to improve drivability performance, comfort, and safety. In the future perspective, the advances in this field will lead these systems to the level of autonomous and cooperative driving, based on sensors networks and sensor fusion. This paper aims to present the readers a novel strategy for lane detection and tracking, which fits as a functional requirement to deploy DAS features like Lane Departure Warning and Lane Keeping Assist. To achieve the presented results, the digital image processing was divided into three levels. At the low-level, the input image dimensionality is reduced from three to one layer, the sharpness is improved, and region of interest is defined based on the minimum safe distance from the vehicle ahead. The feature extractor for lane edges detection design is part of the mid-level processing. The lane tracking strategy development is discussed in the high-level stage; Hough Transform and a shape-preserving spline interpolation are used to achieve a smooth lane fitting. The experimental outcomes were qualitatively and quantitatively evaluated using a ground truth comparison. The strategy shows good accuracy levels, including scenarios with shadows, curves, and road slope.
机译：现代道路车辆利用驾驶员辅助系统（DAS）的功能来改善驾驶性能，舒适性和安全性。从未来的角度来看，基于传感器网络和传感器融合，该领域的进步将使这些系统达到自主和协作驾驶的水平。本文旨在向读者介绍一种新颖的车道检测和跟踪策略，该策略适合部署DAS功能（如车道偏离警告和车道保持辅助）的功能要求。为了获得所提出的结果，数字图像处理被分为三个层次。在低级别，输入图像尺寸从三层减少到一层，清晰度得到改善，并且根据与前方车辆的最小安全距离来定义关注区域。用于车道边缘检测设计的特征提取器是中级处理的一部分。高阶阶段讨论了车道追踪策略的发展；使用Hough变换和形状保留的样条插值来实现平滑的车道拟合。实验结果是使用地面真相比较定性和定量评估的。该策略显示出较高的准确性级别，包括带有阴影，曲线和道路坡度的方案。

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