Investigation of influential factors of tire/pavement noise: A multilevel Bayesian analysis of full-scale track testing data

•The multilevel Bayesian model is more predictive than its frequentist counterpart.•Travel speed dominates over all other factors in tire/pavement noise.•Tire/pavement noise showed significant tire-depending tendency.•Porous pavements are noisier at lower speeds but quieter at higher speeds.•Increased macrotexture depth, vehicle weight, and air humidity associate higher tire/pavement noise. Tire/pavement noise is a primary source of traffic noise that continuously interferes with human life. In this study, we employed a Bayesian multilevel model to reveal the causal relationship between the resulting noise and the considered variables and quantify their uncertainties. The experimental design comprised four primary factors: pavement type, tire type, driving speed, and trailer weight. We also included the impacts of pavement surface characteristics and environmental factors. The results show the proposed Bayesian model is more predictive than its fixed effects counterpart. Among the considered factors, the influence of speed dominates all other factors on the noise levels. The tire/pavement noise increases with macrotexture depth while decreases with the porosity of the surface material. The porous asphalt pavement attenuates noise more significantly at a higher speed. The noise level increases statistically when the tire load increases, while it decreases as the air temperature increases.