Abstract

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of each observed distress, the pavement condition surveys were conducted by actually walking through all the sections. Using these data, PCI was calculated utilizing Micro PAVER software. Dynatest Road Surface Profiler (RSP) was used to collect IRI data of all the sections. Using the SPSS software, linear and nonlinear regressions have been used for developing two models between PCI and IRI based on the collected data. These models have the coefficients of determination (R2) equal to 0.715 and 0.722 for linear and quadratic models. Finally, the results indicate the linear and quadratic models are acceptable to predict PCI from IRI directly.

Highlights

  • Roadway pavements are constructed to provide safe, quick, and comfortable travel

  • The accurate and reliable evaluation of the pavement surface network condition is necessary for an effective pavement management system (PMS) (ASTM, 2017)

  • Various indices, which are used for the evaluation of pavement performance, such as Pavement Condition Index (PCI), International Roughness Index (IRI), Present Serviceability Rating (PSR), Pavement Condition Rating (PCR), etc. have been generally utilized to specify maintenance techniques for the pavements (Shah et al, 2013)

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Summary

INTRODUCTION

Roadway pavements are constructed to provide safe, quick, and comfortable travel. The lack of these features refers to functional insufficiency in the pavement. It is computed through a visual inspection survey method that includes measuring the type, severity, and quantity of each pavement distress (Shahin et al, 1978, Garber and Hoel, 2009). Dynatest Road Surface Profilometer (RSP) system is one of these techniques and is designed to provide high-quality, advanced, automated pavement roughness. This system is regarded as a measurement solution for engineers in the world. The pavement condition surveys to calculate PCI is costly and timeconsuming as compared to IRI

OBJECTIVES
STUDY METHODOLOGY
International Roughness Index Data
DEVELOPMENT MODELS
MODELS VALIDATION
B Models
Findings
10. DISCUSSION
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