IRI Prediction Model for Use in Network-Level Pavement Management Systems
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.
- Record URL:
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Supplemental Notes:
- © 2017 American Society of Civil Engineers.
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Authors:
- Rosa, Francisco Dalla
- Liu, Litao
- Gharaibeh, Nasir G
- Publication Date: 2017-3
Language
- English
Media Info
- Media Type: Web
- Features: References;
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Serial:
- Journal of Transportation Engineering, Part B: Pavements
- Volume: 143
- Issue Number: 1
- Publisher: American Society of Civil Engineers
- EISSN: 2573-5438
- Serial URL: http://ascelibrary.org/journal/jpeodx
Subject/Index Terms
- TRT Terms: Calibration; Pavement management systems; Pavement performance; Roughness; Sensitivity analysis; Subgrade (Pavements); Texture; Traffic loads
- Identifier Terms: International Roughness Index; Texas Department of Transportation
- Subject Areas: Highways; Maintenance and Preservation; Pavements;
Filing Info
- Accession Number: 01642195
- Record Type: Publication
- Files: TRIS, ASCE
- Created Date: Jul 27 2017 10:05AM