2,255
Views
84
CrossRef citations to date
0
Altmetric
Articles

International Roughness Index prediction model for flexible pavements

, , &
Pages 88-99 | Received 28 Jul 2017, Accepted 09 Feb 2018, Published online: 05 Mar 2018
 

Abstract

International Roughness Index (IRI) is a pavement performance indicator which reflects not only the pavement condition but also the ride quality and comfort level of road users. The aim of this paper is to develop an accurate IRI prediction model for flexible pavements using both multiple linear regression analysis and artificial neural networks (ANNs). The models were developed based on the Long-Term Pavement Performance Database. The data were collected for both original and overlaid flexible pavements from the general pavement studies (GPS-1, GPS-2 and GPS-6) and the specific pavement studies (SPS-1, SPS-3 and SPS-5). The final database consisted of 506 sections with 2439 observations. The proposed models (regression and ANNs) predict IRI as a function of pavement age, initial IRI (IRI just after pavement construction), transverse cracks, alligator cracks and standard deviation of the rut depth. The regression model yielded a coefficient of determination (R 2) value of 0.57 while the ANNs model resulted in a much higher R 2 value of 0.75.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.