Can We Predict the Roughness Index (IRI) of a Road Based on its Pavement Condition Index (PCI)?

• Published in: E3S web of conferences Vol. 445; p. 1015
• Main Authors: Pramesti, Florentina Pungky, Setyawan, Ary, Octavian, Muhamad Calvin, Zein, Aditya Putra Muhammad, Safe’i, Kholid Ma’sum, Parnaningrum, Kartika Novianti
• Format: Journal Article
• Language: English
• Published: EDP Sciences 01.01.2023
• ISSN: 2267-1242; 2267-1242
• DOI: 10.1051/e3sconf/202344501015

Road damages might affect pavement condition which leads to reducing the remaining service life of the pavement. Two methods widely known to measure the pavement condition are among others: the Pavement Condition Index (PCI) and the International Roughness Index (IRI). Both intended to measure the functional condition of the pavement. This study aims to show the relationship between PCI and IRI, hence the road roughness can be predicted from on-foot survey measurements. It will start by collecting the distress and its severity parameter as well as the roughness of 6 road sections using Hawkeye mobile car. The car is a complete modular system to measure roughness (using profilometer), capture images and measure the severity of the road distresses and else. The results show that the pavement condition of the 6 sections fall into the category of poor and above. While 44% of the segments are fair. The roughness conditions of all road sections are good or acceptable. The correlation analysis shows that the PCI cannot necessarily explain the IRI, even though both are used to express the functional condition of road pavements, because what Hawkeye measures for the two indices is different.