Pavement frictional behavior affects pavement performance in terms of vehicle safety, fuel consumption, and tire wear. Comprehending and interpreting pavement friction measurements is a challenging task, because of friction sensitivity to several uncontrollable factors. These factors include: pavement surface conditions, such as the type and thickness of contaminants and fluids on the surface and their interaction with friction forces; and the device operating conditions, such as sliding speed, material properties and geometry of the rubber slider used, and operating temperature. Despite the efforts to describe and quantify the impact of varying conditions on pavement friction, which ultimately will allow for a better harmonization of friction measurements, there is a need to better understand the link between the surface texture and physical friction measurements. In this paper, Persson’s friction model is used to analyze and understand the impact of surface texture on frictional behavior of dry pavement surfaces. The model was used to analyze 18 test locations, which were compared with the dry kinetic coefficients of friction (COF) estimated using a British pendulum tester (BPT). The results show that Persson’s friction model could predict the COF estimated from the BPT results with relatively high accuracy. In addition, the model could provide a profound explanation of the frictional forces mechanism. Finally, it was found that the mean profile depth (MPD) cannot provide a full picture of the frictional behavior. However, combining MPD with the Hurst exponent, texture measurements can potentially provide a full physical explanation of the frictional behavior for road surfaces.


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    Title :

    Pavement Friction Modeling using Texture Measurements and Pendulum Skid Tester


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2018-05-05




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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