Road Pavement Condition Index Deterioration Model for Network-Level Analysis of National Road Network Based on Pavement Condition Scanning Data




deterioration, IRI, pavement performance, pavement condition index, PCI, panel data analysis, regression analysis, road condition survey


Surveying the condition of the pavement is one of the most important processes in managing the road network. The information collected during these surveys allows for the calculation of the Pavement Condition Index, which is a derivative cumulative qualitative indicator that evaluates various pavement characteristics and defects. Deterioration modelling of these measured indicators and calculated indices is a critical element and its most accurate prediction brings the process of pavement management closer to a higher quality process by more efficiently allocating funds and repair work. Many different models – both extremely complex and simple – are used in the world to simulate the condition of individual pavement indicators. However, these models are developed based on the data of a certain country or region and are not suitable in another country due to different requirements for pavement structures and other reasons. In Lithuania, measurements of the quality indicators of road surfaces with new generation survey equipment have been carried out recently but the information stored in the databases about road sections is minimal, and it becomes difficult to adapt the models applied abroad due to the missing information. The aim of this study is to create pavement condition index prediction models by evaluating such quantitative and qualitative indicators as traffic loads, road surface unevenness, type of repair, pavement age, climatic zones, and pavement construction classes.


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How to Cite

Paplauskas, P., Vaitkus, A., & Simanavičienė, R. (2023). Road Pavement Condition Index Deterioration Model for Network-Level Analysis of National Road Network Based on Pavement Condition Scanning Data. The Baltic Journal of Road and Bridge Engineering, 18(3), 70-101.