Predicting pavement performance using distress deterioration curves

Predicting pavement performance using distress deterioration curves
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使用破损恶化曲线预测路面性能

DOI:
10.1080/14680629.2023.2238094
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发表时间:
2023
影响因子:
3.7
通讯作者:
Abed A
Abed A
中科院分区:
工程技术3区
文献类型:
--
作者:
Abed A

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英国的公路管理局使用国家公路网路面状况评估(SCANNER)来评估和管理其公路网。该测量车利用激光测量来检测和量化路面上的大部分损坏,例如车辙、裂缝和纹理深度。然而,这是一个数据密集和昂贵的方法,因为它是每年进行一次。这项研究提出了一个简单的方法来预测路面损坏使用以前的扫描仪测量。先前的测量用于开发遇险恶化主曲线(DDMC),其将遇险恶化率与遇险的严重程度相关联。这些曲线可以用来预测未来的损坏严重程度的基础上,目前的状态,而不需要提供进一步的数据,如路面年龄或路面材料性能。为了证明这种方法的应用,我们分析了2014年至2020年期间收集的英国伯明翰郡约400公里A级道路的大量SCANNER数据,并在本研究中对车辙、裂缝强度和纹理深度进行了建模。这些灾害类型的DDMR是根据2014-2018年收集的数据建立的,然后使用2020年的数据来验证预测。结果表明,所开发的方法可以实现在预测路面损坏的道路使用以前的测量,这使得它成为一个有价值的工具,为公路当局受资金不足。
Highway Authorities in the UK use Surface Condition Assessment for the National Network of Roads (SCANNER) in assessing and managing their road networks. This survey vehicle utilises laser measurements to detect and quantify most of the distress on the road surface, such as rutting, cracking and texture depth. It is however a data intensive and expensive approach since it is conducted annually. This study presents a simple method to predict pavement distress using previous SCANNER measurements. The previous measurements are used to develop Distress Deterioration Master Curves (DDMC) that relate distress deterioration rate with the severity of the distress. These curves can be used to predict future distress severity based on the current state without the need to provide further data such as pavement age or pavement material properties. To demonstrate the application of this method, a significant amount of SCANNER data covering around 400 km of class A roads in Nottinghamshire collected between 2014 and 2020 were analysed, and rutting, crack intensity, and texture depth were modelled in this study. DDMRs of these distress types were built based on data collected between 2014-2018, then 2020 data were used to validate the predictions. The results show that the developed method can be implemented in predicting surface distress of roads using previous measurements, which makes it a valuable addition tool for highway authorities subject to underfunding.
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