Mobile Cross-Slope Measurement Method Using Lidar Technology
Mobile Cross-Slope Measurement Method Using Lidar Technology
复制标题
使用激光雷达技术的移动横向坡度测量方法
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
E. Pitts
中科院分区：
文献类型：
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作者：
Y. Tsai;Chengbo Ai;Zhaohua Wang;E. Pitts
有效的横坡有利于公路排水，防止打滑。交通运输机构需要识别和测量具有无效横坡的路段，以便及时进行纠正性维护。然而，交通运输机构使用传统的人工方法来测量数字水平的横向坡度是耗时和劳动密集型的；这些方法不适用于进行网级横向坡度测量。本文提出的移动跨坡测量方法采用新兴的移动激光雷达技术，可以在高速公路速度下准确有效地进行网络级跨坡测量。本文提出的移动坡度测量方法采用了新兴的激光雷达技术（激光雷达校准、数据采集、兴趣区域提取和坡度计算）。进行敏感性研究以确定所提出方法的关键参数（即兴趣区间区域）。通过在受控环境下的测试，验证了所提出方法的准确性和可重复性。实例研究证明了该方法的有效性。对照试验结果表明，该方法在三次运行中，与数字级测量值的平均测量差为0.088，重复性良好，标准偏差小于0.038。实例研究结果表明，该方法可在高速公路上运行，在路网级跨坡充分性评价中具有良好的应用前景。
An effective cross slope facilitates drainage on highways and prevents hydroplaning. There is a need for transportation agencies to identify and measure road sections that have noneffective cross slopes so that timely corrective maintenance can be performed. However, the traditional manual methods used by transportation agencies to measure cross slopes with a digital level are time-consuming and labor intensive; these methods are not feasible for conducting a network-level cross-slope measurement. A proposed mobile cross-slope measurement method uses emerging mobile lidar technology that can accurately and effectively conduct network-level cross-slope measurement at highway speeds. The proposed mobile cross-slope measurement method uses emerging lidar technology (lidar calibration, data acquisition, region of interest extraction, and cross-slope computation). A sensitivity study was conducted to determine the key parameter (i.e., the region of interest interval) for the proposed method. The accuracy and the repeatability of the proposed method were critically validated through testing in a controlled environment. A case study demonstrated the capability of the proposed method. The results from the controlled test show that the proposed method can achieve desirable accuracy with an average measurement difference of 0.088 from the digital-level measurements and a desirable level of repeatability with a standard deviation of less than 0.038 in three runs. The results of the case study show that the proposed method can be operated at highway speed and is promising for the assessment of network-level cross-slope adequacy.