| Safe roads require pavement surfaces that provide adequate friction to tires, helping to bring vehicles to a complete stop in a timely manner that avoids accidents. The current manual methods of evaluating surface friction of roads and bridges are not only dangerous for the inspectors and motorists on the road but they are also very time-consuming and subject to inspector's judgment. This thesis confirms the possibility of monitoring friction of pavement through pavement macrotexture from acoustic measurements underneath the body of a moving vehicle. Currently, macrotexture is quantified by a Mean Texture Depth (MTD) index. In the present work, MTD is estimated from the sound generated by the tire-pavement interaction in a moving vehicle. To establish this approach, experiments were performed at the National Center for Asphalt Technology in Auburn, Alabama. Signal processing techniques were used to identify a frequency band that led to an accurate correlation between integrated acoustic pressure and MTD. This frequency band depends on the speed of the vehicle and the pavement macrotexture. The effect of microphone locations and the speed of the vehicle on macrotexture monitoring are studied and conclusions are presented. It is observed that raising the microphones by 13 inches decreased correlation by approximately 13%. Microphones that are close and pointing towards contact patch of rear tire have highest correlation to MTD. Also, it is concluded that correlation increases with vehicle speed. Accurate estimates of MTD were obtained for road surfaces having MTD values in the range of 0.5--2.5 mm with vehicle speeds in the range of 32--80 km/h (20--50 mph). |
