## 4 Discussion
### Limitations of This Study and Further Studies  
In this study, only the contrast values were compared by measuring the luminance values for pedestrian targets at 3000 K and 6000 K, and in some bad weather test conditions, the contrast was higher at 3000 K than at 6000 K. In this case, it is thought that a comparative experiment is necessary to confirm whether the pedestrian's target is more visible at 3000 K than at 6000 K even to the human eye. When conducting an experiment through the participation of a large number of participants, it is necessary to organize various participants in consideration of the appropriate number of participants, gender, age, etc. In particular, it is necessary to study how the color temperature variable headlamp affects the visibility of the elderly. In this case, it may be necessary to consider the characteristics of the eyes according to the age of the person. In addition, it appears that it is necessary to consider not only visual effects but also non-visual effects when conducting experiments with participants. This is to consider not only the CCT variable from the viewpoint of improving visibility, but also the effect of \begin{table}
\begin{tabular}{c c c c} \hline
**Weather Condition** & **Target Position** & **White Target (\%)** & **Black Target (\%)** \\ \hline \multirow{3}{*}{Rain 20 mm/h} & 5 m & \(-3.33\) & 8.3 \\ \cline{2-4}  & 12.5 m & 13.05 & 15.09 \\ \cline{2-4}  & 25 m & \(-3.33\) & \(-6.8\) \\ \hline \multirow{3}{*}{Rain 50 mm/h} & 5 m & 13.15 & 37.58 \\ \cline{2-4}  & 12.5 m & 22.15 & 2.34 \\ \cline{1-1} \cline{2-4}  & 25 m & \(-27.71\) & \(-12.33\) \\ \hline \end{tabular}
\end{table} 
Table 14: 3000 K contrast ratio compared to 6000 K in rain conditions. a characteristic of a specific color temperature on a person (driver). For example, if bluish color temperature improves driver alertness when driving at night to prevent drowsy driving and helps drivers make good decisions in emergency situations, then it can also help drive safely. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Test Case**} & \multicolumn{2}{c}{**Weather Condition**} & & & \multicolumn{2}{c}{**Contrast Comparison Result**} \\  & & **Level** & **Target Position** & **Color** & **Temperature** & **(High, Low)** \\ \cline{2-6}  & **Weather Type** & **(Visibility Distance 40 m,** & **(5 m, 12.5 m, 25 m)** & **(5000 K, 6000 K)** & **White Target** & **Black Target** \\  & **(Clear, Fog, Rain)** & **((  
In this case, the effect of metamerism according to the characteristics of the light source and the reflector can also be considered. In the case of light sources, the same CCT can be implemented in various ways, and metamerism can be affected accordingly. In particular, the use of a spectral camera can be a method to analyze the characteristics of light sources by wavelength band, and there is a case of using a hyperspectral camera in the image recognition field to distinguish between the street lights and the headlights of vehicles [31]. Research is needed not only from the point of view of the human eye in bad weather at night, but also from the point of view for improving the recognition performance of sensors for automobiles. In particular, it is necessary to study technologies and evaluation methods for overcoming bad weather from the standpoint of autonomous driving systems. Of course, it is also necessary to study backscattering in dense fog conditions. In this regard, as mentioned in the introduction section, several studies have been conducted [15; 16; 17]. In view of this, it is expected that progress will be ultimately made through sensor-integrated headlamps with respect to issues related to backscattering. To this end, a sensor-integrated headlamp in which a lidar, camera, or radar is integrated into a headlamp assembly is being developed [32; 33], and it is considered that an evaluation method is needed from the viewpoint of human visibility and the recognition performance of the systems.