A state-of-the-art review of parameters influencing measurement and modeling of skid resistance of asphalt pavements. (1st July 2016)

• Record Type: Journal Article
• Authors: Kogbara, Reginald B.; Masad, Eyad A.; Kassem, Emad; Scarpas, A. (Tom); Anupam, Kumar
• Is Part Of: Construction & building materials. Volume 114(2016)
• Page Start: 602
• Page End: 617
• Publication Date: 2016-07-01
• Subjects: Aggregate properties -- Asphalt mixtures -- Skid resistance -- Surface texture -- Friction; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2016.04.002
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: A state-of-the-art review of skid resistance of asphalt pavements is presented. Key parameters influencing skid resistance measurement and modeling are discussed. Details modeling efforts entailing different aspects of tire-pavement interaction. Frictional performance of asphalt pavements largely depends on coarse aggregates. Some research gaps and ongoing efforts to address some of the gaps are identified. Abstract: A state-of-the-art review of key parameters that influence measurement and modeling of skid resistance of asphalt pavements is provided. Tire-pavement interaction/friction is discussed and the current harmonization method of friction measurements questioned. The latest developments on pavement surface texture measurement and characterization are highlighted. A critical review of aggregate properties affecting friction, the frictional properties of asphalt mixtures and the influence of environmental factors on skid resistance is presented. An overview of modeling efforts entailing different aspects of tire-pavement friction is also presented. The frictional performance of asphalt pavements largely depends on the type and quality of coarse aggregates used. The different hot mix asphalt (HMA) classifications generally have similar microtextures. Their frictional performance follows the same order as their macrotextures. There is need for experimentally-validated skid resistance prediction models, especially for warm surfaces. Such models should account for tire and pavement surface texture characteristics, and the influence of environmental factors. Some other research needs are also identified.