TECHNICAL PAPERS
Mar 23, 2011

Development of a Model for Asphalt Pavement Skid Resistance Based on Aggregate Characteristics and Gradation

Publication: Journal of Transportation Engineering
Volume 137, Issue 12

Abstract

Many research studies and field experiences have shown a strong relationship between wet-weather accidents and pavement skid resistance. Therefore, measurement methods and models are needed to evaluate the safety level of driving on an asphalt pavement surface during its service life. The objective of this study was to develop a skid resistance prediction model based on measurable quantities such as aggregate shape characteristics, aggregate gradation, aggregate resistance to polishing, and traffic level. To achieve this objective, the skid number (SN) of asphalt pavement sections and traffic data were acquired and analyzed. In addition, statistical analysis was conducted to determine the relationship between different aggregate properties, pavement surface characteristics, and the measured SN values. The aggregate properties were measured using conventional test methods (acid insolubility, magnesium soundness, micro-Deval, and British polish value), and the Aggregate Imaging System (AIMS). The pavement surface characteristics were measured using the dynamic friction tester and circular texture meter. The statistical analysis led to the development of a new model for predicting the asphalt pavement SN as a function of traffic level, initial and terminal aggregate texture values measured using AIMS, and aggregate gradation described using the two-parameter Weibull distribution function.

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Information & Authors

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Published In

Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 137Issue 12December 2011
Pages: 863 - 873

History

Received: Mar 27, 2010
Accepted: Mar 21, 2011
Published online: Mar 23, 2011
Published in print: Dec 1, 2011

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Authors

Affiliations

Arash Rezaei [email protected]
Graduate Research Assistant, Zachry Dept. of Civil Engineering, Texas A&M Univ., 3135 TAMU, College Station, TX 77843 (corresponding author). E-mail: [email protected]
Eyad Masad, Ph.D., F.ASCE [email protected]
P.E.
Professor, Zachry Dept. of Civil Engineering, Texas A&M Univ., 3136 TAMU, College Station, TX 77843-3136. E-mail: [email protected]
Arif Chowdhury [email protected]
Assistant Research Engineer, Texas Transportation Institute, Texas A&M Univ., 3135 TAMU, College Station, TX 77843-3135. E-mail: [email protected]

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