| Pavement profiles generally have many of the statistical properties of random signals, it is difficult to distinguish the different surfaces mathematically based on the factors of construction date of a road, daily traffic conditions, etc. To further understand the features of polishing process on pavement surfaces, experimental texture measurements and Data Dependent Systems (DDS) approach were utilized to model and analyze the elevation profiles collected from polished and unpolished aggregate surfaces of Aggregate Wear Index (AWI) wear track. The sampling step size was explored carefully to determine which sampling step size could reveal the properties of tire polishing process. The DDS approach was then used to model and analyze those elevation profiles. It was found that the DDS approach was able to capture both the characteristics of the evolved macrotexture and microtexture and the polishing effect on the aggregate surfaces is found to reduce the macrotexture roughness significantly. The second part in this thesis is to exhibit a texture analysis from several bituminous pavement surfaces obtained from Michigan. Since traffic abrades the pavement surface, exposing aggregates and makes aggregates worn and polished, the polishing properties of coarse aggregates play a significant role in determining skid resistance. Therefore, 1 micron step size scan was used to collect the elevation profile from exposed aggregates and 45 micron step size scan was arranged to collect data from texture surface on each core surface, respectively. DDS approach was utilized to model and analyze the data for both 1 micron and 45 micron step size scans. The characteristics of both microtexture and macrotexture were derived by applying different criteria to DDS modeling analysis and they were correlated to the British Pendulum Tester numbers (BPNs) Laboratory Friction Tester values (LBF) obtained on the same core. A good correlation was found from some mixed type of pavements. |
