Enhancement of Network Level Macrotexture Measurement Practices through Deterioration Modeling and Comparison of Measurement Devices for Integration into Pavement Management Systems

This research sought to integrate measurement and prediction of surface macrotexture for use in pavement management systems. This was achieved through two experiments, the first modeled the behavior of a binder-rich stone matrix asphalt when subjected to traffic loading using a heavy vehicle simulator to report the effect on pavement macrotexture. The second experiment compared high-speed macrotexture measurement devices on a variety of surfaces and under various operating conditions. The change in macrotexture due to traffic loading showed that as the cumulative load increased, the macrotexture decreased due to bleeding on the pavement's surface. A regression model determined that, on average, the macrotexture's root mean square (RMS) decreased 0.14 mm per million equivalent single axle load applied. A comparison of RMS and mean profile depth (MPD) outputs indicated that RMS was more sensitive to changes in macrotexture due to bleeding. In comparing devices, pairwise device agreement was evaluated using a Limits of Agreement. The results demonstrate good repeatability for each of the devices tested. The agreement analysis showed that not all high-speed devices can be used interchangeably for all pavement surfaces. Data acquisition speed was found to be a factor in macrotexture parameter calculation for two of the devices. The effect of speed was found to be worse on randomly textured surfaces than on transversely textured surfaces.