Ahmed Abed
Predicting pavement performance using distress deterioration curves
Abed, Ahmed; Rahman, Mujib; Thom, Nick; Hargreaves, David; Li, Linglin; Airey, Gordon
Authors
Mujib Rahman
Dr NICK THOM NICHOLAS.THOM@NOTTINGHAM.AC.UK
ASSISTANT PROFESSOR
Dr DAVID HARGREAVES DAVID.HARGREAVES@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Linglin Li
Professor GORDON AIREY GORDON.AIREY@NOTTINGHAM.AC.UK
PROFESSOR OF PAVEMENT ENGINEERING MATERIALS
Abstract
Highway Authorities in the UK use Surface Condition Assessment for the National Network of Roads (SCANNER) in assessing and managing their road networks. This survey vehicle utilises laser measurements to detect and quantify most of the distress on the road surface, such as rutting, cracking and texture depth. It is however a data intensive and expensive approach since it is conducted annually. This study presents a simple method to predict pavement distress using previous SCANNER measurements. The previous measurements are used to develop Distress Deterioration Master Curves (DDMC) that relate distress deterioration rate with the severity of the distress. These curves can be used to predict future distress severity based on the current state without the need to provide further data such as pavement age or pavement material properties. To demonstrate the application of this method, a significant amount of SCANNER data covering around 400 km of class A roads in Nottinghamshire collected between 2014 and 2020 were analysed, and rutting, crack intensity, and texture depth were modelled in this study. DDMRs of these distress types were built based on data collected between 2014-2018, then 2020 data were used to validate the predictions. The results show that the developed method can be implemented in predicting surface distress of roads using previous measurements, which makes it a valuable addition tool for highway authorities subject to underfunding.
Citation
Abed, A., Rahman, M., Thom, N., Hargreaves, D., Li, L., & Airey, G. (2024). Predicting pavement performance using distress deterioration curves. Road Materials and Pavement Design, 25(6), 1174-1190. https://doi.org/10.1080/14680629.2023.2238094
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 13, 2023 |
Online Publication Date | Sep 13, 2023 |
Publication Date | Jun 2, 2024 |
Deposit Date | Jun 6, 2024 |
Publicly Available Date | Jun 7, 2024 |
Journal | Road Materials and Pavement Design |
Print ISSN | 1468-0629 |
Electronic ISSN | 2164-7402 |
Publisher | Taylor and Francis |
Peer Reviewed | Peer Reviewed |
Volume | 25 |
Issue | 6 |
Pages | 1174-1190 |
DOI | https://doi.org/10.1080/14680629.2023.2238094 |
Public URL | https://nottingham-repository.worktribe.com/output/35141731 |
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Predicting pavement performance using distress deterioration curves
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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