This paper describes the development of a new method to analyse and interpret road surface roughness data for establishing ride quality for the purpose of managing pavements. The method uses numerical models of particular vehicle types along with the Hilbert Transform to predict
variations in vibration magnitude which is used as an indicator of road surface quality or rideability. The paper shows how rough patches or segments along a pavement can be detected by identifying statistically stationary sections within the profile. The paper also compares this newly
introduced method with the International Roughness Index (IRI). It is shown how the calculation of the statistical distribution of the Vibration Intensity affords a practical means to describe the overall quality of both short road segments and large road networks. Finally, a statistical model, based on a modified Rayleigh distribution, is proposed as a new alternative to characterising ride quality and pavement roughness.