In times of steadily increasing traffic loads and extreme weather phenomena, the safe maintenance of infrastructure poses a difficult challenge to operators, especially when a vast number of aged structures exists and fundamental data is missing. This paper addresses the demand for cost-efficient deformation monitoring of anchored retaining structures along public roads. The principal idea is to process laser scans of a motor-vehicle-based mobile mapping system with a high degree of automation. Starting with scene interpretation, our processing pipeline extracts the retaining wall from the rest of the point cloud, segments the anchored elements, and computes their deformations. This method requires, however, correcting for positioning errors to obtain accurate results. We exploit the high data redundancy of road patches and line markings for alignment. Due to the high degree of automation, computations scale to large numbers of point clouds and run in a repeatable manner. Even when traveling along highways with up to 100 km/h, we achieve repeatable accuracies for tilting and lateral displacements that compare to traditional, labor-intense surveying methods.

中文翻译：

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用于沿公路锚固结构的大规模变形监测的移动激光扫描数据处理

在不断增加的交通负荷和极端天气现象的时期，基础设施的安全维护给操作员带来了艰巨的挑战，特别是当存在大量陈旧的结构并且缺少基本数据时。本文提出了对沿公共道路锚固支护结构进行具有成本效益的变形监测的需求。主要思想是高度自动化地处理基于机动车辆的移动制图系统的激光扫描。从场景解释开始，我们的处理管道从其余点云中提取挡土墙，对锚定元素进行分段，并计算其变形。但是，该方法需要校正定位误差以获得准确的结果。我们利用道路斑块和线路标记的高数据冗余度进行对齐。由于高度的自动化，计算可扩展到大量点云并以可重复的方式运行。即使在时速高达100 km / h的公路上行驶时，与传统的劳动密集型测量方法相比，我们仍可实现可重复的倾斜和横向位移精度。