为实现沥青路面坑槽深度、面积和体积等多维度指标的自动、准确检测，利用三维激光技术对室内坑槽模型进行扫描，基于Matlab软件对激光点云数据采用不规则三角网(TIN)平面插值法重构了坑槽三维模型，进而结合等高线提取确定了坑槽边界，实现了坑槽多维度指标自动计算；对比了不同坑槽多维度指标计算误差，研究了激光线纵向间距对计算误差影响规律.研究结果表明：坑槽深度、面积和体积指标的最大相对误差分别为3.96%、4.58%和4.74%；当激光线纵向间距从1 mm逐渐增大至20 mm时，坑槽多维度指标计算相对误差逐渐增加；当间距为5 mm时，坑槽深度、面积和体积指标的最大相对误差分别为4.65%、6.32%和7.17%；当间距大于5 mm后，坑槽三维重构模型逐渐失真并出现了部分缺失，从而导致多维度指标检测误差的增大；因此，为保证坑槽多维度指标检测准确度建议激光线纵向间距应不大于5 mm；坑槽多维度指标准确获取将为路面破损层位判定、严重程度评价和修补材料估算提供依据.
In order to automatically and accurately achieve multi-dimensional indexes such as depth, area and volume of the asphalt pavement pothole, the advanced three-dimensional line laser technology was used to scan indoor potholes with different sizes. The laser point cloud data collected was processed using the triangulated irregular network(TIN) plane interpolation method by Matlab software and was used to reconstruct the three-dimensional pothole model. Combined with contour extraction method, the pothole border was identified and multidimensional indexes of pothole were automatically calculated. The relative error of different pothole multi-dimensional indexes was compared and the effect of laser’s longitudinal spacing on relative error was studied. The results show that the maximum relative error of the pothole depth, area and volume are 3.96%, 4.58% and 4.74%, respectively. The relative error of pothole multi-dimensional index decreases with the increases of pothole size. When laser’s longitudinal spacing increases from 5 mm to 20 mm, the relative error of pothole multi-dimensional index increases by degrees. The maximum relative error of pothole depth, area and volume are 4.65%, 6.32% and 7.17%, respectively, when spacing is 5 mm. The relative error of pothole multi-dimensional indexes increases significantly when spacing becomes larger than 5 mm. Therefore, to insure the accuracy of multi-dimensional index detection, it is suggested that laser’s longitudinal spacing is less than 5 mm. The method of pothole multi-dimensional index accurately provides foundation for the pavement structural layers identification of damage distribution, evaluation of distress severity and estimation of materials rehabilitation.