Development of Statistical Wet Weather Model to Evaluate Frictional Properties at the Pavement-Tire Interface on Hot-Mix Asphalt Concrete

Skid resistance on wet pavements is influenced by friction at the tire-pavement interface as well as overall hot mix asphalt (HMA) performance. It is important to control aggregate, asphalt, and mix properties to achieve desirable frictional properties on HMA during its service life. Thus, it is important to identify and control these properties through an effective testing and monitoring program. There is also a need for upgrading current testing criteria and aggregate classification systems in view of new techniques that can be used either as replacements and/or supplements to current tests. This project, a part of the Texas Department of Transportation (TxDOT) current research program to evaluate inadequacies of current tests to skid performance, focuses on tests evaluating aggregate shape and distribution parameters. In this project, a wet weather test selection criteria was developed to evaluate the effectiveness of current and new testing techniques to monitor aggregate shape, texture, and distribution characteristics. Extensive tests conducted on 40 aggregates selected from the TxDOT Quality Material Catalog covered various parts of the U.S.A. Fine aggregate tests, including the Uncompacted Void Content, the Compacted Aggregate Resistance, the Methylene Blue, and the Particle Size Analysis, were performed to evaluate angularity, texture, and distribution characteristics within fine aggregates. Flat and elongated tests on coarse aggregates used both conventional and automated techniques to analyze shape and size distribution characteristics. A statistical analysis was performed to select tests that would enable monitoring of aggregate shape and distribution properties enhancing skid performance. The evaluation criteria were based upon a sensitivity and correlation analysis to evaluate consistency, reproducibility, and ability of tests to effectively discern aggregates with good and marginal performance.