Characterization and modeling of textured cement concrete pavement surfaces for tire-pavement noise prediction

In rapidly urbanizing regions, tire-pavement interaction is increasingly recognized as a significant contributor to traffic noise pollution. Cement concrete pavements, widely used in urban roadways, are known for their durability and load-bearing capacity, but they also contribute significantly to traffic noise. This noise stems from the pavement’s inherent rigidity, which enhances vibrations when tires come into contact, and its smooth surface, which reflects sound waves back into the environment, amplifying the overall noise level. To mitigate this issue, researchers have turned to innovative texture techniques to produce quieter surfaces. This study introduces a 3D modeling technique for concrete pavement surfaces, analyzing textures in multiple driving directions using 2D profile data. Texture profiles are extracted from the wheel tracks, and average profile levels are calculated from eight test sites. Through correlation analysis between measured tire-pavement noise and texture profile levels, the high-frequency texture, mid-frequency texture, and low-frequency texture are considered as indicators of tire-pavement noise. A multivariate regression model links these noise levels to specfic texture profile levels:high:$L_{\mathrm{tx},0.21.25}$, mid:$L_{\mathrm{tx},1.68}$, and low:$L_{\mathrm{tx},1040}$. By incorporating noise assessments from concrete pavements into the design process, the model contributes to the optimized design and construction of quieter pavement textures.