Characterizing road roughness by wavelet transform

Abstract

Summary roughness statistics are commonly used by highway agencies to characterize road roughness profiles to provide convenient numerical indices for pavement performance monitoring and management planning. Many different roughness indices have been used by different highway agencies worldwide. Unfortunately, since different indices are computed with different considerations and mathematical procedures, they often do not correlate with one another well. This presents a practical problem for exchange of information and experience among practitioners or highway agencies. A proposal is presented for the use of wavelet transform to overcome this problem. Wavelet transform can represent detailed pavement roughness features of different wavelengths quantitatively in terms of wavelet energy. The usefulness of wavelet transform representation of pavement roughness profiles was studied by analyzing the roughness data of 200 flexible pavement and 200 rigid pavement sections. Comparisons were made with four common roughness indices, namely, the international roughness index (IRI), root-mean-square vertical acceleration (RMSVA), mean absolute vertical acceleration (MAVA), and slope variance (SV). It was found that IRI, RMSVA, MAVA, and SV had pairwise coefficients of multiple determination (R 2) ranging from 0.18 to 0.75. But wavelet energy statistics had an R 2 of at least 0.857 with each of the roughness indices. Therefore, wavelet energy statistics can be a useful common basis to relate different forms of pavement roughness measures.