Recent research has shown that wet weather crashes are influenced by the macrotexture of the pavement surface. Therefore, availability of such data in pavement management systems would help highway agencies assess the adequacy of pavement surface macrotexture and determine if corrective actions are required. Methods commonly used for measuring macrotexture are cumbersome, time-consuming, provide information on a limited portion of the pavement surface, and expose workers to risk. Methods for measuring network-level macrotexture are currently available. However, there is a potential for enhancing available procedures or developing new procedures to provide a better characterization of pavement surface texture. Research is needed to (1) identify the factors that influence texture measurement, (2) develop improved methods for network-level macrotexture measurement that address these factors, and (3) prepare recommended test methods, equipment specifications, and data quality assurance practice to facilitate use of these methods. This information will help highway agencies collect reliable network-level macrotexture data for use in pavement management systems and decision making.
The objective of this research is to develop recommended protocols for test methods, equipment specifications, and data quality assurance practice for network-level macrotexture measurement.