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Multi-lanes detection based on panoramic camera

机译:基于全景摄像机的多车道检测

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The lane detection system is one of the most important subsystems to achieve the environmental perception of autonomous vehicles. This paper addresses the problem of detecting multiple lanes in a relatively large range around the autonomous vehicle without making too much approximation on the shape of the lane marks. A panoramic camera and a LIDAR is used to obtain a wide range of image information and exclude part of the interference information. The vertical lane marks with specific width is extracted by a filter with 2D Gaussian kernel. In order to describe the lanes with relatively complex shapes like variable curvature curves, the model of equidistant curves is proposed and a robust detection method of equidistant curves is designed under the guidance of the lane model. Satisfactory experimental results in diverse environment and the successful application on autonomous vehicles demonstrate the effectiveness of the proposed method.
机译:车道检测系统是实现自动驾驶汽车环境感知的最重要子系统之一。本文解决了在自动驾驶车辆周围较大范围内检测多个车道而又不对车道标志的形状过于近似的问题。全景相机和激光雷达用于获取广泛的图像信息,并排除部分干扰信息。具有特定宽度的垂直车道标记由具有2D高斯核的滤波器提取。为了描述诸如变曲率曲线等相对复杂形状的车道,提出了等距曲线模型,并在车道模型的指导下设计了鲁棒的等距曲线检测方法。在不同环境中的令人满意的实验结果以及在自动驾驶汽车上的成功应用证明了该方法的有效性。

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