Predicting Pavement Performance Using Distress Deterioration Curves

Ahmed Abed*, Mujib Rahman, Nick Thom, David Hargreaves, Linglin Li, Gordon Airey

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
JournalRoad Materials and Pavement Design
Early online date13 Sept 2023
Publication statusE-pub ahead of print - 13 Sept 2023

Bibliographical note

© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Funding: Engineering and Physical Sciences Research Council [grant number EP/T01962X/1]


  • Pavement performance
  • deterioration curves
  • distress prediction
  • modelling


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