Geometric texture indicators for safety on AC pavements with 1 mm 3D laser texture data

Abstract Surface texture and friction are two primary characteristics for pavement safety evaluation. Understanding their relationship is critical to reduce potential traffic crashes especially at wet conditions. Texture data obtained from existing systems are restricted on either a small portion on pavement surface or one line-of-sight profile, and the currently used texture indicators, such as Mean Profile Depth (MPD), and Mean Texture Depth (MTD) only reveal partial aspects of texture property. With the emerging 3D laser imaging technology, acquiring full-lane 3D pavement surface data at sub-millimeter resolution and at highway speeds has been made possible via the newly developed PaveVision3D Ultra data collection system. In this study using 1 mm 3D data collected from PaveVision3D Ultra, four types of texture indicators (amplitude, spacing, hybrid, and functional parameters) are calculated to represent various texture properties for pavement friction estimation. The relationships among those texture indicators and pavement friction are examined. MPD and Skewness – two height texture parameters, Texture Aspect Ratio (TAR) – a spatial parameter, and Surface Bearing Index (SBI) – a functional parameter are found to be the four most contributing parameters for pavement friction prediction. Finally a multivariate regression model is developed based on residual plot analysis methods to estimate pavement friction with the R-squared value of 0.95. This study would be beneficial in the continuous measurement and evaluation of pavement safety for project- and network-level pavement surveys.

[1]  Roger S Walker,et al.  Texture measurement and friction estimation using laser data acquisition and neural networks , 2007 .

[2]  Susan L. Tighe,et al.  Pavement Surface Mixture, Texture and Skid Resistance: A Factorial Analysis , 2008 .

[3]  Kevin K McGhee,et al.  High-speed texture measurement of pavements. , 2003 .

[4]  T Kuennen.  CREATING FRICTION WHERE RUBBER MEETS THE ROAD , 2003 .

[5]  V. Janoo,et al.  PERFORMANCE TESTING OF HOT-MIX ASPHALT AGGREGATES , 1999 .

[6]  Arash Rezaei,et al.  Predicting Asphalt Mixture Skid Resistance by Aggregate Characteristics and Gradation , 2009 .

[7]  J. J. Henry,et al.  EVALUATION OF PAVEMENT FRICTION CHARACTERISTICS , 2000 .

[8]  J Olek,et al.  RELATING SURFACE TEXTURE OF RIGID PAVEMENT WITH NOISE AND SKID RESISTANCE , 2004 .

[9]  Luis Alvarez,et al.  Formalization and computational aspects of image analysis , 1994, Acta Numerica.

[10]  Tien Fang Fwa,et al.  Effect of Aggregate Spacing on Skid Resistance of Asphalt Pavement , 2003 .

[11]  Kelvin C. P. Wang,et al.  Potential Measurement of Pavement Surface Texture Based on Three-Dimensional Image Data , 2012 .

[12]  Chih-Ling Tsai,et al.  The examination of residual plots , 1998 .

[13]  Ulf Sandberg.  Influence of road surface texture on traffic characteristics related to environment, economy and safety : A state-of-the-art study regarding measures and measuring methods , 1998 .

[14]  Yves Delanne,et al.  Prediction of Tire/Wet Road Friction from Road Surface Microtexture and Tire Rubber Properties , 2004 .

[15]  K J Stout,et al.  Development of methods for the characterisation of roughness in three dimensions , 2000 .

[16]  Thomas J. Yager,et al.  MACROTEXTURE AND DRAINAGE MEASUREMENTS ON A VARIETY OF CONCRETE AND ASPHALT SURFACES , 1982 .

[17]  O. Panagouli,et al.  Fractal Evaluation of Pavement Skid Resistance Variations. I: Surface Wetting , 1998 .

[18]  S Iyinam,et al.  Prediction of Road Surface Friction Coefficient Using Only Macro- and Microtexture Measurements , 2005 .

[19]  Ahmed Shalaby,et al.  Mean Profile Depth of Pavement Surface Macrotexture Using Photometric Stereo Techniques , 2007 .

[20]  Brian D Prowell,et al.  Evaluation of Circular Texture Meter for Measuring Surface Texture of Pavements , 2005 .

[21]  J J Henry,et al.  PREDICTION OF SKID RESISTANCE AS A FUNCTION OF SPEED FROM PAVEMENT TEXTURE MEASUREMENTS , 1978 .