Prediction models for distress noise generated due to tire-pavement surface interaction

Abstract

The major objective of this research is to assess the distress noise generated due to tire-pavement surface interaction for different modes and to evolve a noise prediction model for any manner taking into consideration the different factors impacting the distress noise generation. Seven flexible and four rigid pavement roads were chosen for the calculation of the noise in Baghdad city. Tire-pavement interaction noise was calculated using Onboard Sound Intensity (OBSI) Method by restricting the noise generated from the vehicle exhaust and the engine systems. Prediction models were developed for assessing tire pavement noise from vehicle speed, pavement age, wheel load, mean texture depth (MTD) and pavement distresses. Four statistical models were obtained from this research to assess the distress noise generated due to tire-pavement surface interaction using linear regression stepwise method. These models showed the effect of different types of distresses in addition to the factors that have been taken into consideration on tire pavement noise. Vehicle speed was the greatest considerable variable influencing the noise generated due to tire-pavement surface interaction. Some distresses and factors have been excluded from the models due to their poor relationship with tire-pavement noise. These models have been categorized based on the type of pavement surface (flexible or rigid) and the presence or absence of pavement distresses. The predicted statistical models were verified with calculation, by comparing the data estimated by the models and data form field tests. Therefore, it can be used as a method of detecting distresses rather than visual inspection.