Pavement macro-texture analysis using wavelets

Abstract

This paper utilises a wavelet approach to interpret the macro-texture data collected on asphalt and concrete pavement surfaces with a wide range of macro-texture properties. The experimental data were obtained using a circular track meter (CTMeter) device on pavements built at the Virginia's Smart Road test facility. The size of the data-set allowed nine levels of wavelet decomposition with wavelengths ranging from 1.7 to 435 mm. The extent of macro-texture variation was summarised using the normalised wavelet energy metric defined as the sum of the squares of the detailed wavelet coefficients for the sub-bands that correspond to the macro-texture range of wavelengths divided by the length of the test section expressed in mm²/m. This metric was found highly correlated with the empirical mean profile depth measurements. Hence, the wavelet approach can be used to objectively analyse CTMeter measurements of pavement texture.

Keywords:

• pavements
• macro-texture
• aggregates
• wavelet energy

Acknowledgements

The authors would like to express their sincere thanks to the Center for Sustainable Transportation Infrastructure of the Virginia Tech Transportation Institute (VTTI) for supplying the data analysed. The authors also acknowledge with gratitude the paper reviewers for their valuable and constructive comments.