Title: On the use of non-Gaussian models for statistical description of road micro-surface profiles
Authors: Alexander Steinwolf; Matthias Wangenheim; Joerg Wallaschek
Addresses: AST Consulting Ltd., 14A Croydon Road, Auckland 0600, New Zealand ' Institute of Dynamics and Vibration Research, Leibniz University of Hannover, Appelstr. 11, 30167 Hannover, Germany ' Institute of Dynamics and Vibration Research, Leibniz University of Hannover, Appelstr. 11, 30167 Hannover, Germany
Abstract: When analysing vehicle-road interaction, probability density function (PDF) of random micro-surface is required. Since the asperity tops are polished by tyres stronger than the valley bottoms, the surface height profiles become asymmetrical. As a result, the PDFs of micro-surface signals are often different from the Gaussian model and one needs a non-Gaussian PDF model operating with skewness and kurtosis. Previous solutions by the Pearson and Johnson distributions do not lend themselves for further implementation in analytical form. To overcome this difficulty, a non-Gaussian PDF can be constructed from a few Gaussian sections with different mean values and standard deviations. To use such a piecewise-Gaussian model for analytical derivations, it is simply necessary to apply the classic Gaussian equation several times. An example of skewed PDF of micro-surface of an asphaltic concrete highway measured by a laser scanning system was adequately approximated by the tetra-Gaussian model consisting of four Gaussian sections.
Keywords: vehicle-road interaction; random micro-surface; probability density function; non-Gaussian; skewness; kurtosis.
International Journal of Vehicle Systems Modelling and Testing, 2019 Vol.13 No.3, pp.260 - 274
Received: 22 Sep 2018
Accepted: 14 Jan 2019
Published online: 12 Aug 2019 *