Various means of extracting road boundary from mobile laser scanning data based on vehicle trajectories have been investigated. Independent of positioning and navigation data, this study estimated the scanner ground track from the spatial distribution of the point cloud as an indicator of road location. We defined a typical edge block consisting of multiple continuous upward fluctuating points by abrupt changes in elevation, upward slope, and road horizontal slope. Subsequently, such edge blocks were searched for on both sides of the estimated track. A pseudo-mileage spacing map was constructed to reflect the variation in spacing between the track and edge blocks over distance, within which road boundary points were detected using a simple linear tracking model. Experimental results demonstrate that the ground trajectory of the extracted scanner forms a smooth and continuous string just on the road; this can serve as the basis for defining edge block and road boundary tracking algorithms. The defined edge block has been experimentally verified as highly accurate and strongly noise resistant, while the boundary tracking algorithm is simple, fast, and independent of the road boundary model used. The correct detection rate of the road boundary in two experimental data is more than 99.2%.

中文翻译：

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使用激光扫描仪地面轨迹从MLS数据中提取道路边界

已经研究了基于车辆轨迹从移动激光扫描数据中提取道路边界的各种方法。独立于定位和导航数据，本研究根据点云的空间分布估计扫描仪地面轨迹，作为道路位置的指标。我们通过海拔、上升坡度和道路水平坡度的突然变化定义了一个典型的边缘块，由多个连续的向上波动点组成。随后，在估计轨迹的两侧搜索这样的边缘块。构建了一个伪里程间距图以反映轨道和边缘块之间的间距随距离的变化，在该范围内使用简单的线性跟踪模型检测道路边界点。实验结果表明，提取的扫描仪的地面轨迹正好在路面上形成一条平滑连续的线；这可以作为定义边缘块和道路边界跟踪算法的基础。定义的边缘块已被实验验证为高精度和强抗噪性，而边界跟踪算法简单、快速且独立于所使用的道路边界模型。两次实验数据中道路边界的正确检测率均在99.2%以上。并且独立于所使用的道路边界模型。两次实验数据中道路边界的正确检测率均在99.2%以上。并且独立于所使用的道路边界模型。两次实验数据中道路边界的正确检测率均在99.2%以上。