## 2 Materials and Methods
### Data Preparation and Processing
#### 2.4.1 Experiment Data Preparation
In particular, the unexpected increases observed in laser intensity values at specific distances reflect the stabilizing influence of LIDAR's multi-channel structure on measurements. In the study conducted by [PERSON] et al., both indoor and outdoor tests were conducted to investigate the impact of environmental conditions on laser intensity measurements. The outdoor tests aimed to assess the effects of atmospheric factors such as sunlight, wind, and other environmental influences on laser intensity. These tests were performed in an open field measuring 25 m \(\times\) 5.5 m, where measurements were taken using three different panel types (SW-Gloss, SB-Gloss, and SB-Matt) at varying distances. The study reported that, while both indoor and outdoor measurements exhibited similar trends in laser intensity values, the intensity values recorded in indoor tests were higher due to the absence of atmospheric effects. This difference was attributed to the fact that indoor measurements serve as a reference dataset, free from environmental interference, thereby providing a controlled experimental baseline [6]. Although measurements were conducted at different distances and for various colors in the open-field tests, this article provides detailed results only for the indoor and outdoor measurements of the SW-Gloss surface at a distance of 10 m. This study observed a consistent ratio between indoor and outdoor intensity values for the SW-Gloss surface and assumed that this ratio could also be applicable to other surfaces and distances. Based on the data presented in this study, the relationship between laser intensity values in indoor and outdoor conditions was generalized for different distances and surface colors. Figure 5a illustrates the indoor and outdoor measurements for the SW-Gloss surface at a distance of 10 m, while Figure 5b presents the corresponding intensity ratios between these two conditions. This ratio was utilized as a scaling coefficient to adjust the indoor laser intensity data to match outdoor conditions. This generalization was made based on the findings of [PERSON] et al., which indicated that similar trends were observed across different surfaces and distances. The derived coefficients were determined for use in the analysis and modeling of laser intensity values. The reflectivity coefficient values for the paint colors used in this study were based on optical properties obtained from sources such as NASA ECOSTRESS [22], USGS High Resolution Spectral Library [23], [PERSON] et al. 's study [13], [PERSON] et al. 's study [24], and [PERSON] et al. 's review [12]. However, since the exact specifications of the paints used in the experiments are not known, reflectivity coefficients were determined based on the properties of the pigments and materials commonly used for these colors in the automotive industry. This approach ensured that the reflectivity coefficient values obtained were consistent with real-world applications. In the automotive industry, paint pigments play a critical role in the aesthetic appearance and durability of vehicles. Generally, the pigments used have a dual function in terms of providing coloring and protective properties [24]. Table 2 provides details of these key parameters used to analyze the effects of different paint colors on laser intensity.