Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters

Author:

Ban Ivana1,Deluka-Tibljaš Aleksandra1ORCID,Ružić Igor1ORCID

Affiliation:

1. Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia

Abstract

The importance of skid resistance performance assessment in pavement engineering and management is crucial due to its direct influence on road safety features. This paper provides a new approach to skid resistance predictive model definition based on experimentally obtained texture roughness parameters. The originally developed methodology is based on a photogrammetry technique for pavement surface data acquisition and analysis, named the Close-Range Orthogonal Photogrammetry (CROP) method. Texture roughness features were analyzed on pavement surface profiles extracted from surface 3D models, obtained by the CROP method. Selected non-standard roughness parameters were used as predictors in the skid resistance model. The predictive model was developed by the partial least squares (PLS) method as a feature engineering procedure in the regression analysis framework. The proposed model was compared to the simple linear regression model with a traditional texture parameter Mean Profile Depth as the predictor, showing better predictive strength when multiple non-standard texture parameters were used.

Publisher

MDPI AG

Reference73 articles.

1. Determination and prediction of pavement skid resistance–connecting research and practice;Fwa;J. Road Eng.,2021

2. Theory of rubber friction and contact mechanics;Persson;J. Chem. Phys.,2001

3. On the nature of surface roughness with application to contact mechanics, sealing, rubber friction and adhesion;Persson;J. Phys. Condens. Matter,2005

4. Rubber friction, tread deformation and tire traction;Heinrich;Wear,2008

5. (2004). Characterization of Pavement Texture by Use of Surface Profiles—Part 1: Determination of Mean Profile Depth (Standard No. EN ISO 13473-1).

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