Pavement performance modeling

Pavement performance models could be developed to predict a single distress such as a crack or the aggregate pavement condition index.
Schematic deterioration of the condition of a road over time
The increase in the IRI of a road in Texas. The blue dots on the curve represent maintenance actions.

Pavement performance modeling or pavement deterioration modeling is the study of pavement deterioration throughout its life-cycle.[1][2] The health of pavement is assessed using different performance indicators. Some of the most well-known performance indicators are Pavement Condition Index (PCI), International Roughness Index (IRI) and Present Serviceability Index (PSI),[3][4] but sometimes a single distress such as rutting or the extent of crack is used.[2][5] Among the most frequently used methods for pavement performance modeling are mechanistic models, mechanistic-empirical models,[6] survival curves and Markov models. Recently, machine learning algorithms have been used for this purpose as well.[3][7] Most studies on pavement performance modeling are based on IRI.[8]

  1. ^ Ford, K., Arman, M., Labi, S., Sinha, K.C., Thompson, P.D., Shirole, A.M., and Li, Z. 2012. NCHRP Report 713 : Estimating life expectancies of highway assets. In Transportation Research Board, National Academy of Sciences, Washington, DC. Transportation Research Board, Washington DC.
  2. ^ a b Piryonesi, Sayed Madeh (November 2019). Piryonesi, S. M. (2019). The Application of Data Analytics to Asset Management: Deterioration and Climate Change Adaptation in Ontario Roads (Doctoral dissertation) (Thesis).
  3. ^ a b Piryonesi, S. M.; El-Diraby, T. E. (2020) [Published online: December 21, 2019]. "Data Analytics in Asset Management: Cost-Effective Prediction of the Pavement Condition Index". Journal of Infrastructure Systems. 26 (1). doi:10.1061/(ASCE)IS.1943-555X.0000512. S2CID 213782055.
  4. ^ Way, N.C., Beach, P., and Materials, P. 2015. ASTM D 6433–07: Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys.
  5. ^ Ens, A. (2012). Development of a flexible framework for deterioration modelling in infrastructure asset management.
  6. ^ AASHTO. 2008. Mechanistic-empirical pavement design guide: A manual of practice.
  7. ^ "Piryonesi, S. M., & El-Diraby, T. (2018). Using Data Analytics for Cost-Effective Prediction of Road Conditions: Case of The Pavement Condition Index:[summary report] (No. FHWA-HRT-18-065). United States. Federal Highway Administration. Office of Research, Development, and Technology". Archived from the original on 2019-02-02.
  8. ^ Cite error: The named reference :02 was invoked but never defined (see the help page).