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New lane detection algorithm for autonomous vehicles using computer vision

机译:使用计算机视觉的自主车辆新车道检测算法

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For navigation tasks it is necessary to determine position of the ego vehicle relative to the road. One of the principal approaches is to detect road boundaries and lanes using a vision system in the vehicle. This paper presents a simple and robust method designed to detect and estimate the curvature of road lane boundaries from images provided by a monocular camera. First, we use Vector-lane-concept and Non-uniform B-Spline (NUBS) interpolation method to construct the boundaries road lane. Based on lane detection result, we estimate the curvature of left and right lane boundaries for Autonomous Guided Vehicle systems application. Some experimental results based on real world road images are presented. These simulation results show the efficiency, feasibility and robustness of the algorithm.
机译:对于导航任务,有必要确定自我车辆相对于道路的位置。其中一个主要方法是使用车辆中的视觉系统检测道路边界和车道。本文介绍了一种简单且坚固的方法,旨在检测和估计来自单眼相机提供的图像的道路车道边界的曲率。首先,我们使用矢量车道概念和非均匀B样条(NUB)插值方法来构建边界道路车道。基于车道检测结果,估计自主引导车辆系统应用的左右车道边界的曲率。提出了基于现实世界道路图像的一些实验结果。这些仿真结果表明了算法的效率,可行性和鲁棒性。

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