The interaction between heavy vehicle and road surface roughness results in vibrations that detract from the perceived comfort of the driver, and generate dynamic wheel loads which are believed to increase pavement wear. This paper describes the methodology for assessing the viability of a new profile-based index (Pit) developed in previous work, as a predictor of the magnitude of dynamic wheel loads, and discusses the results. In the previous work, roughness content in the waveband 4.8-19.5 m correlated best with the mean ratings of ride quality by a panel of truck drivers. When travelling at normal highway speeds, roughness wavelengths in this band excite the low frequency vibration modes of the heavy vehicle body. As these modes are considered to be the major contributors to dynamic wheel loading of road pavements, it was hypothesised that the PIt could also be a good predictor of the magnitude of the dynamic wheel loads. Computer simulations of the dynamic wheel loads were carried out by using a full vehicle model and the profiles of 10 pavement sections as the excitation inputs. Tests of the PIt proved that it is a good predictor of the dynamic loading of some road pavements. However, careful examination of the data resulted in identifying another profile index, the overall root mean square of profile elevation, that provides good predictions of the magnitude of dynamic wheel loads for all pavement sections considered in this study. The variable sub-grade and climate conditions between the test sections influence the extent of long wavelength roughness development and, ultimately, the excitation levels of the low frequency vibration modes of the truck body. One-third octave band analysis was used to study the effects of these factors on the dynamic behaviour of road pavements. (a).
Samenvatting