Characterisation and generation of road surface roughness for improved tyre-road interaction models

Predicting friction between rubber and road surfaces requires accurate characterisation of the contact. Theoretical models for tyre-road contact, friction and wear typically assume that asphalt surfaces can be characterised as having Gaussian and/or homogeneous roughness properties, yet scans of real road surfaces do not support these assumptions. Additionally, higherfidelity numerical models of contact, such as those based on Boussinesq solutions or finite element modelling, require representative surfaces larger than individual surface scans can provide, motivating the need to generate representative surfaces for use in such models. This paper presents methods to better characterise and generate large scale, non-Gaussian, inhomogeneous rough surfaces similar to asphalt based on the characteristics found in small-scale surface scans. Using the measured height probability distribution, power spectral density, and the surface’s gradient distribution we show how it is possible to create virtual surfaces with a spatial distribution of features that is faithful to the original surface. Moreover, we present an approximation that allows the estimation of reduced-noise two-dimensional power spectral densities from single line scans to be used to create these virtual surfaces. Combination of these techniques allows large-area virtual surfaces to be created from limited measured data including surface line scans, allowing for low cost, speedy and faithful surface reconstruction. Such surfaces allow for improved high fidelity physical modelling of tyre friction, wear, and sound reflection/absorption