Development of a Relationship between Pavement Condition Index and International Roughness Index in Rural Road Network
Development of a Relationship between Pavement Condition Index and International Roughness Index in Rural Road Network
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农村路网路面状况指数与国际粗糙度指数关系的发展
DOI：
10.1155/2021/6635820
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发表时间：
2021
影响因子：
1.8
通讯作者：
Reza Salehfard
中科院分区：
文献类型：
--
作者：
Sasan Adeli;Vahid Najafi moghaddam Gilani;Mohammad Kashani Novin;Ehsan Motesharei;Reza Salehfard
本文的主要目的是探讨农村公路网的PCI和IRI值之间的关系。为此，选择了伊朗农村公路网的6000个路面路段。使用自动车收集路面图像和粗糙度线性轮廓，以分别计算PCI和IRI。三个指数回归模型，并在三个不同的IRI间隔验证。结果表明，指数回归模型是IRI与PCI的最佳关联模型。在这些模型中，R2值被认为是可以接受的，等于0.75，0.76，和0.59的道路质量良好，公平，和非常差，分别表示一个良好的关系IRI和PCI。验证结果表明，该模型具有较高的精度。此外，IRI和PCI之间的关系变得越来越弱，作为增加路面粗糙度的结果，这可能是由于故障的数量和严重程度的增加。此外，还分析了两次R.C.在研究的道路中很少观察到车辙。因此，所提出的模型更适用于没有上述故障的道路和沥青路面农村公路网。
The main objective of this paper was to investigate the relationship between PCI and IRI values of the rural road network. To this end, 6000 pavement sections of the rural road network in Iran were selected. Road surface images and roughness linear profiles were collected using an automated car to calculate PCI and IRI, respectively. Three exponential regression models were developed and validated in three different IRI intervals. Analysis of the results indicated that exponential regression was the best model to relate IRI and PCI. In these models, R2 values were found to be acceptable, equal to 0.75, 0.76, and 0.59 for roads with good, fair, and very poor qualities, respectively, indicating a good relationship between IRI and PCI. Moreover, validation results showed that the model had a high accuracy. Also, the relation between IRI and PCI became weaker as a result of increasing the level of road surface roughness, which can be caused by the increase in the number and severity of failures. Furthermore, two failures of rail R.C. and rutting were rarely observed in the studied roads. Therefore, the proposed model is more applicable for roads without the mentioned failures and asphalt-pavement rural road network.