# Effect of Mixture Design Parameters of Stone Mastic Asphalt Pavement on Its Skid Resistance
## 1 Introduction  
Skid resistance refers to the friction force that prevents the tire from slipping along the pavement surface [1]. It had been shown that the traffic accident risk increased significantly when the skid resistance was below a certain threshold value [2]. Therefore, skid resistance of the pavement is an important design parameter affecting driving safety. Skid resistance/friction force consists of adhesion and hysteresis, mainly depending on the surface texture of the pavement [3; 4; 5; 6]. The surface texture is classified according to wavelengths, including microtexture (0-0.5 mm), macrotexture (0.5-50 mm), megatexture (50-500 mm), and unevenness (500 mm to 50 m) [7]. The skid resistance of the pavement mainly depends on its microtexture and macrotexture. It is generally considered that the microtexture characterized by the friction coefficient plays a major role in skid resistance at low speeds; that the macrotexture characterized by mean texture depth (MTD), mean profile depth (MPD) or sensor measured texture depth (SMTD) has a great influence on the skid resistance at high speeds [8]. There are still no effective methods to accurately characterize microtexture until now. A number of studies used the British pendulum tester (BPN) to characterize microtexture and evaluate skid resistance at low speeds [9; 10]. [PERSON] et al. found that the friction coefficient measured by BPN was significantly affected by macrotexture. Hence, the general view that skid resistance of the pavement mainly depends on its microtexture is not always right [11]. Additionally, a dynamic friction tester (DFT) and a grip tester were also used to evaluate skid resistance at low speeds [12; 13]. As mentioned previously, a number of parameters were applied to characterize the macrotexture of the pavement surface. These parameters could be obtained by different methods. [PERSON] et al. used the circular track meter (CTM), laser inertial road profiler, and a sand patch to measure the pavement texture, and used MPD and MTD to characterize the macrotexture of stone mastic asphalt (SMA) and open-graded friction course (OGFC). Then, the correlation of parameters obtained by different test methods was established [14]. The stationary laser profilometer (SLP) was applied to obtain the texture elevation of the pavement surface and the texture spectral characteristics by digital signal processing. Simultaneously, the formulas of texture indicators with different wavelength ranges were proposed [15]. The texture elevation of the pavement surface could be also obtained by laser texture scanners (LTS), and geometrical indicators were used to characterize macrotexture, including MPD, average roughness, leveling depth, mean depth, surface roughness depth, and peak to valley height [16]. However, CTM, SLP, and LTS are quite expensive. In light of expensive devices measuring pavement texture, three dimensional (3D) measurements by stereophotogrammetry or microscopy were considered to characterize macrotexture of pavement surface [17; 18; 19; 20]. Compared with using two-dimensional (2D) line profiles, measurements in 3D can accurately characterize the roughness of the pavement surface. Firstly, a large amount of data from multiple images can be collected; secondly, 3D models of the pavement surface were established by some software, such as Digital Surf MountainsMap, 3D flow Zephyr, etc; finally, roughness parameters (arithmetic mean skewness, kurtosis, height, etc) were calculated. These parameters could be used to evaluate microtexture, macrotexture, and megatexture. Asphalt pavement consists of asphalt and aggregates with different sizes [21; 22; 23; 24; 25; 26; 27; 28]. Its texture is affected by many factors, such as aggregates type, aggregates sizes, mixture type, etc. Previous studies focused on how to characterize pavement surface texture and the influence of different factors (coarse aggregates type, mixture type, etc) on skid resistance.