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DOI: 10.15862/05angTS416 (https://doi.org/10.15862/05angTS416)

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Uglova E.V., Saenko S.S. [Review of longitudinal pavement roughness prediction tools] Russian Journal of Transport Engineering, 2016, Vol. 3, No. 4. Available at: https://t-s.today/PDF/05angTS416.pdf (in Russian). DOI: 10.15862/05angTS416

Review of longitudinal pavement roughness prediction tools

Uglova Evgenia Vladimirovna
Don state technical university, Russia, Rostov-on-Don
E-mail: uglova.ev@yandex.ru

Saenko Sergey Sergeevich
Don state technical university, Russia, Rostov-on-Don
E-mail: svkube@mail.ru

Abstract. Many road agencies use special tools for managing their assets. Article provides overview of most known pavement management systems. Most of all describing pavement management systems have special tools for prediction longitudinal roughness, rutting, friction, Pavement Conditional Index (PCI), Surface Distress Index (SDI), Structural Adequacy Index (SAI) and Ride Comfort Index (RCI) etc. Among the factors of performance deterioration the following external factors are the most frequently singled out: the number of freezing and thawing cycles, temperature, humidity, precipitation, ground water depth level, the number of traffic load repeats in daily average annual traffic intensity or equivalent single axle load (ESAL); internal factors: material type, structural strength and thickness, subgrade material, etc. There is an analysis of current longitudinal roughness prediction models, which are used on the project and network level, in the article. The article contains deterministic models of longitudinal roughness prediction suggested by Russian and foreign authors at different periods of times.

Keywords: pavement management system; prediction models; pavement performance; roughness

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