The long wavelength roughness (LWR) in the longitudinal profile of a pavement surface occurs as a result of the heave or subsidence of the subgrade soil. LWR excites the low frequency vibrational modes of the heavy vehicle body including body bounce. The resulting vibrations detract from the perceived ride quality and result in high dynamic wheel loads generated at the pavement-tyre interface. The LWR cannot be detected by the established measures of roughness such as the International Roughness Index (IRI). This paper describes the development of a new profile-based index that can detect LWR and better represents the truck ride in addition to providing a better indicator of the road sections subject to high dynamic wheel loads. A panel of heavy vehicle drivers were asked to rate the ride quality using a five points scale on a number of marked road sections with different levels of roughness. Power spectral density (PSD) analyses of road surface profile data of the rating sections were used to identify the waveband of road roughness that correlates best with Mean subjective panel ratings (MPR). The content of road roughness in the waveband 4.8-19.5m resulted in the highest correlation and was used to develop the new index. The index, denoted Profile Index (PI) is the root mean square (RMS) average of the RMS values computed for the outer and inner wheel path profiles in the best band. Then the PIs of all the rating sections and their MPRs were used to develop a statistical transform termed 'Truck Ride Number, TRN' that predicts heavy vehicle ride from profile measurement. Scales of the acceptable and unacceptable values of TRN and PI were developed for use by pavement engineers to identify road sections that are rough to heavy vehicle drivers and adopt the appropriate rehabilitation programs to fix it. (a)
Samenvatting