Journal of Engineering Research
Journal of Engineering Research. 2024; 3: (3) ; 10.12208/j.jer.20240037 .
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国家能源集团陕西神延煤炭有限责任公司 陕西榆林
*通讯作者： 雷志勇,单位：国家能源集团陕西神延煤炭有限责任公司 陕西榆林；
针对可通行区域中道路路边提取问题，在仅三维激光雷达点云作为输入情况下，提出了一种基于人工特征提取的路边检测方法。该方法通过检测道路路边点来获得道路的可通行区域。对于道路路边检测，提出了一种动基点和基轴法，该方法时刻选定新的基点与基轴，使得基轴与基点能够灵活调整方向与位置，从而提高非直道路路边点分类及提取的准确率。并采用了最小二乘法对路边点集合进行曲线拟合获得光滑的道路延展趋势，实现了平面道路路边曲线的稳定输出。此外为了解决帧间的波动问题，将卡尔曼滤波算法用于道路边缘的跟踪识别，通过构建预测和观测模型，实现了对路边点的稳定输出，确保系统在不同车速和道路状况下的可靠性。
Aiming at the problem of roadside extraction in passable area, a method based on artificial feature extraction is proposed by using only three-dimensional LIDAR point cloud. The method obtains the accessible area of the road by detecting the roadside points. For roadside detection, a moving base-point and base-axis method is proposed, which selects a new base-point and base-axis at all times, so that the base-axis and base-points can flexibly adjust the direction and position to improve the accuracy of the classification and extraction of non-straight roadside points. And the least squares method is used to the roadside point collection curve fitting to obtain the smooth road extension trend, which realizes the stable output of the plane roadside curve. In addition, in order to solve the fluctuation problem between frames, Kalman filtering algorithm is used for tracking and identification of road edges, and by constructing the prediction and observation model, the stable output of roadside points is realized, which ensures the reliability of the system under different vehicle speeds and road conditions.
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