Optimization of pavement texture depth measurement using machine learning algorithms

Key Points

• The research aims to enhance the accuracy of pavement texture depth measurements through machine learning techniques.
• Used 3D laser scanning for measurement
• Applied paired t-tests and ANOVA for data analysis
• Employed machine learning algorithms for depth prediction
• Separated macrotexture and microtexture using Power Spectral Density
• Improved measurement accuracy of pavement texture depth
• Successful separation of macrotexture and microtexture studies
• Demonstrated the effectiveness of machine learning in predicting pavement depth