Pavement performance modeling
Appearance
![]() | This article or section is in a state of significant expansion or restructuring. You are welcome to assist in its construction by editing it as well. If this article or section has not been edited in several days, please remove this template. If you are the editor who added this template and you are actively editing, please be sure to replace this template with {{in use}} during the active editing session. Click on the link for template parameters to use.
This article was last edited by Pirehelokan (talk | contribs) 6 years ago. (Update timer) |
Pavement performance modeling is the study of pavement deterioration throughout its life-cycle. 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)[1]. Among the most frequently used methods for pavement performance modeling are mechanistic, mechanistic-empirical models[2], survival curves and Markov models. Recently, machine learning algorithms have been used for this purpose as well.[3]
History
References
- ^ Way, N.C., Beach, P., and Materials, P. 2015. ASTM D 6433–07: Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys.
- ^ AASHTO. 2008. Mechanistic-empirical pavement design guide: A manual of practice.
- ^ "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".
{{cite web}}
: Cite has empty unknown parameter:|dead-url=
(help)