IRI Prediction Model for Use in Network-Level Pavement Management Systems
Publication: Journal of Transportation Engineering, Part B: Pavements
Volume 143, Issue 1
Abstract
This paper describes the development and validation of an empirical model for predicting the International Roughness Index (IRI) over time. The model is designed to balance mathematical complexity and ease of implementation in network-level pavement management systems. The predicted pavement roughness is modeled as a function of the initial IRI (post construction or treatment) and pavement age. The model accounts for the effects of climate, subgrade, treatment type, pavement type, traffic loading, and functional system (urban or rural) through the use of calibration coefficients. Representative roadway sections are selected from a 10-year (2005 to 2014) pavement management database provided by the Texas Department of Transportation (TxDOT). To validate the model, the IRI data observed in 2015 is compared with the 2015 predicted IRI. The reasonableness and sensitivity of the model are also evaluated. The results show that the proposed model can be a useful tool for predicting IRI in network-level pavement management systems.
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Acknowledgments
The authors wish to express their gratitude to CAPES/Brazil for support through postdoctoral scholarship process number 99999.006732/2014-03.
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part B: Pavements
Volume 143 • Issue 1 • March 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Aug 22, 2016
Published in print: Mar 1, 2017
Accepted: Apr 24, 2017
Published online: May 11, 2017
Discussion open until: Oct 11, 2017
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