# A Simulation of Tire Hydroplaning Based on Laser Scanning of Road Surfaces
## 3 Test Methods
### Simulation Model
#### 3.2.2 Road Surface Modeling  
The laser scanning instrument mentioned above was used to collect the THREE-DIMENSIONAL data of the road surface, and the texture information of AC-13, SMA-13 and OGFC-13 road surfaces was obtained. The following is the complete process of the road surface THREE-DIMENSIONAL model construction:  
1. Surface point cloud information processing. Using a laser texture measuring instrument to linearly measure the surface of each asphalt mixture rut, we obtained elevation information of the road surface texture with a data point interval of 0.05 mm, which is the point cloud data. The point cloud data were then exported as a.csv file; before reconstruction, preprocessing of the point cloud data is required. First, due to alternating measurement paths, the order of adjacent scan segments must be adjusted to ensure consistent point cloud sorting. Second, because the laser beam may produce multiple reflections in the texture gaps, some elevation information cannot be collected, and the system assigns these values to the scan limit value, forming \"out-of-limit points\". To ensure reconstruction accuracy, the number of out-of-limit points should be controlled within 5% of the total number of points; if exceeded, a re-scan is necessary. For identified out-of-limit points, linear interpolation using adjacent valid points is used for correction. The above processing is implemented through MATLAB, ultimately obtaining high-precision point cloud data. Taking the AC-13 pavement as an example, its point cloud imported into CAD appears as shown in Figure 10a. 2. Reverse reconstruction of pavement point cloud information. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Material Parameter** & \begin{tabular}{c} **Cross-Sectional** \\ **Area (mm2)** \\ \end{tabular} & **GAP (mm)** & **Angle (\({}^{\circ}\))** & \begin{tabular}{c} **Modulus (105** \\ **MPa)** \\ \end{tabular} & **Poisson Ratio** & \
\begin{tabular}{c} **Density** \\ **(g/cm3)** \\ \end{tabular} \\ \hline
\begin{tabular}{c} Tire cord 1 \\ Tension wire 2 \\ Tension wire skeleton \\ \end{tabular} & 0.212 & 1.16 & 70 & 1.722 & 0.3 & 5.9 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Parameters of carcass material for radial tires. Figure 9: Tire finite element model. During the process of reconstructing the road surface in reverse, point cloud data are processed using reverse modeling techniques to construct a simulation model that closely matches the actual road surface structure. This paper employs Geomagic Studio software (Version 12(r)) developed by Geomagic to achieve the three-dimensional reconstruction of point cloud data. The software supports the automatic conversion of point clouds into polygonal meshes, mesh simplification, and polygon-to-NURBS surface conversion, and can be exported in various standard formats such as STL, IGES, STEP, and CAD files. Taking the AC-13 pavement as an example, the reconstruction process is divided into three stages: point cloud processing, polygon processing and accurate surface fitting. 1. Point cloud processing  
After the collected point cloud data are imported into Geomagic Studio, coloring processing is required to improve visibility, and then the point cloud is encapsulated into an initial polygonal mesh, as shown in Figure 10b. 2. Polygon processing  
Automatic triangulation is used to generate polygonal surface patches for the road. Due to the complex texture of the road surface, sharp points or error points may occur during the triangulation process. The \"Mesh Doctor\" tool is used to remove abnormal patches, and a curvature-based local filling method is employed to repair defects, ensuring mesh continuity and obtaining a complete triangular mesh model, as shown in Figure 10c. 3. Exact surface fitting  
After obtaining the mesh model, the geometry profile is constructed and NURBS surface fitting is performed by editing the contour lines and surface segments to make fine adjustments.