Traffic noise mitigation through texture-induced quiet pavement: Analytical modeling and field test

Abstract

Tire-pavement noise is a major contributor to traffic noise pollution, impacting human health and well-being. The advent of 3D printing and prefabrication technologies makes it feasible to economically produce delicate concrete pavement textures for noise mitigation. However, relationships between the noise and texture characteristics (e.g., cavity shape, width, depth, and spacing) remain unknown. This study developed an analytical model for tire-pavement noise and calibrated/validated the model using On-board Sound Intensity tests on a purposely constructed road section with manufactured texture configurations. These textures were found to be capable of reducing the noise level by 8–15 dB(A) over conventional concrete textures, and the model prediction closely matched experimental data. Subsequently, the model was used to investigate the texture-noise relationships and identify those major influencing factors. This study contributes to tire-pavement noise modeling and offers insights for building quieter concrete pavements and enhancing the urban living environment.