Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

Muataz Safaa Abed

doi:10.31026/j.eng.2020.12.05

Article Details

Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

Authors:

Muataz Safaa Abed

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.26 Issue 12, pp.81-94

Document Type:

Article

Publication Date:

1/2020

Document Language:

English

Document ID (Org No.):

2001381506

pISSN:

2520-3339

DOI:

10.31026/j.eng.2020.12.05

Keywords:

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.

Article Details

Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

Authors:

Muataz Safaa Abed

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.26 Issue 12, pp.81-94

Document Type:

Article

Publication Date:

1/2020

Document Language:

English

Document ID (Org No.):

2001381506

pISSN:

2520-3339

DOI:

10.31026/j.eng.2020.12.05

pavement evaluation

International Roughness Index

Pavement Condition Index

pavement roughness

Issues

Article Details

Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

Authors: Muataz Safaa Abed

Publisher: University of Baghdad

Journal: Journal of Engineering Vol.26 Issue 12, pp.81-94

Document Type: Article

Publication Date: 1/2020

Document Language: English

Document ID (Org No.): 2001381506

pISSN: 2520-3339

DOI: 10.31026/j.eng.2020.12.05

pavement evaluation

International Roughness Index

Pavement Condition Index

pavement roughness

Issues

Authors:

Muataz Safaa Abed

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.26 Issue 12, pp.81-94

Document Type:

Article

Publication Date:

1/2020

Document Language:

English

Document ID (Org No.):

2001381506

pISSN:

2520-3339

DOI:

10.31026/j.eng.2020.12.05