## 3 Methods for the Characterisation and Evaluation of the Skid Resistance of Asphalt Pavements
### Pavement Macro- and Microtexture Measurement Methods  
#### 3.2.1. Pavement Texture Measurement Methods  
(1) Laser scanning measurement method  
The laser texture scanning method employs a laser transmitter to emit a laser beam onto the pavement surface and to receive the reflected laser beam from another angle. This enables the construction depth of the pavement to be accurately and rapidly determined. However, the equipment required for this method is expensive and it is not possible to measure the pavement when it is submerged in water [58]. The most commonly used laser texture scanning instruments are circular texture meters (CTMs) [59] and laser texture scanners (LTSs), as shown in Figure 5. A CTM is a fixed-point, non-contact laser texture testing device. The CTM measures the road surface profile at 0.868 mm intervals along a circular path with a diameter of 286 mm. The CTM device rotates at a speed of 0.1 m-s-1 to generate 8 segments of contour lines of the road surface and stores the data in a portable computer. Based on these contour lines, two different pavement macrotexture indices can be calculated: the mean section depth and the root mean square of the contour [60; 61]. The LTS is capable of measuring the macrotexture and microtexture of pavements in a straightforward manner and with an excellent resolution. (2) Image processing methods  
The image processing method is based on the principle of diffuse reflection. Intelligent devices such as high-definition cameras are employed to obtain the three-dimensional parameters of the structure of the road surface. The digital images are then converted into grey-scale images by computer algorithms. The combination of pavement textures was quantitatively analysed by image processing methods [62]. The efficacy of image processing methods is contingent upon a multitude of variables, including lighting conditions, road conditions, camera positions, and other factors [63]. Despite this, image processing methods are identified by their accuracy, the quantity of information they yield, and their ease of operation, as shown in Figure 6.  
Figure 5: Laser scanning measuring equipment. (3) CT scanning method  
The CT scanning method utilises industrial CT to obtain three-dimensional morphology images of asphalt mixtures. This is achieved through the use of software to screen, distinguishing between coarse and fine aggregates, asphalt binder, and other substances formed by the texture condition [64]. The CT equipment is illustrated in Figure 7. The CT scanning method is more accurate but is limited to indoor measurements with inefficient detection [65]. (4) Mechanical stylus method  
The mechanical stylus method works by moving the tip of a stylus over the road surface at a certain speed, and the computer uses sensors to detect the undulation signals of the road surface, which contain the macroscopic texture of the road surface; the working principle is shown in Figure 8. The mechanical stylus method offers several advantages, including high data accuracy, reliable and stable measurement outputs, excellent repeatability, minimal sensitivity to environmental conditions, and straightforward instrument operation. However, this technique also presents certain limitations: it is susceptible to causing surface scratches on the measured object, exhibits relatively low scanning speeds, and is constrained by a limited measurable area [66]. The measurement accuracy of the mechanical stylus method is 0.02 to 5 \(\upmu\)m. The detection error rate of the mechanical stylus  
Figure 6: Road surface texture laser detection. Figure 7: ZEISS Xradia Versa X-ray microscopes. method is related to the size and hardness of the stylus, the signal acquisition technology, and the speed of movement. (5) Sand patch method (SPM)  
The sand patch method (SPM) evaluates pavement macrotexture by distributing a known volume of sand onto the surface and measuring the diameter of the sand-covered area.