Abstract

Ride quality, safety, and tire pavement noise are functional performance measures of concern to highway motorists. Owing to the significant influence of surface macrotexture on wet-weather skid resistance, splash and spray, and highway traffic noise, a need exists for reliable and repeatable methods to measure pavement macrotexture over the road network. To address this need, the National Cooperative Highway Research Program sponsored a project that developed draft protocols for test methods, equipment specifications, and data quality assurance practices for network-level macrotexture measurement. The project conducted three field experiments to evaluate available technologies in regard to repeatability, agreement, and accuracy. This paper focuses on the field experiment conducted at the Texas A&M University RELLIS Campus, which aimed to validate macrotexture measurements from high-speed laser equipped devices suitable for network-level macrotexture data collection and processing. To accomplish this objective, the RELLIS experiment included test speed and laser exposure time in the test matrix, fabricated a measurement beam to collect static reference texture data using a high-resolution laser, and compared texture measurements from different devices with corresponding reference values. This paper presents the findings and conclusions drawn from the RELLIS experiment.

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