A review on pavement distress and structural defects detection and quantification technologies using imaging approaches

Pavement distress detection(PDD)plays a vital role in planning timely pavement maintenance that improves pavement service life.In order to promote the development of PDD technologies and find out the insufficiencies in PDD field,this paper reviews the technical development history and characteristics of various PDD technologies,which contributes to the current state of research on PDD.First,processes of PDD are briefly introduced.The PDD technologies based on radar ranging,2D image,laser ranging and 3 D structured light are illustrated.The newest 3D PDD technology based on interference fringe,which has better accuracy,is in progress.The principles and implementation processes of these methods are discussed.Finally,the shortcomings of these technologies in the field of PDD are concluded.Recommendations for future development are provided.The research results show that various PDD technologies have been continuously improved,developed,over the past decade,and have achieved a series of results.However,the measurements from existing PDD technologies can not be metrological traced to acquire the true dimensions of pavement distresses.The lack of metrological traceability technology in the PDD field needs to be further solved.In order to achieve more accurate and efficient PDD,the metrological traceability technology of PDD systems has become the future development direction in this field.

Influence of computation algorithm on the accuracy of rut depth measurement

Rutting is one of the dominant pavement distresses, hence, the accuracy of rut depth measurements can have a substantial impact on the maintenance and rehabilitation （M 8： R） strategies and funding allocation. Different computation algorithms such as straight- edge method and wire line method, which are based on the same raw data, may lead to rut depth estimation which are not always consistent. Therefore, there is an urgent need to assess the impact of algorithm types on the accuracy of rut depth computation. In this paper, a 1B-point-based laser sensor detection technology, commonly accepted in China for rut depth measurements, was used to obtain a database of 85,000 field transverse profiles having three representative rutting shapes with small, medium and high severity rut levels. Based on the reconstruction of real transverse profiles, the consequences from two different algorithms were compared. Results showed that there is a combined effect of rut depth and profile shape on the rut depth computation accuracy. As expected, the dif- ference between the results obtained with the two computation methods increases with deeper rutting sections： when the distress is above 15 mm （severe level）, the average dif- ference between the two computation methods is above 1.5 mm, normally, the wire line method provides larger results. The computation suggests that the rutting shapes have a minimal influence on the results. An in-depth analysis showed that the upheaval outside of the wheel path is a dominant shape factor which results in higher computation differences.