## 5 Conclusions  
The severity of traffic accidents is high in bad weather situations such as rain and fog, but there is no standard for evaluating road lighting in bad weather, and there is little research related to road lighting that can reduce this. The existing road lighting performance evaluation method is based on normal standards measures of road surface luminance through a luminance meter, which is a method that cannot be used in bad weather. Therefore, in this study, obstacle recognition distance was proposed as a way to evaluate the performance of road lighting in bad weather, and the following results were derived through an empirical experiment using subjects to determine whether obstacle recognition distance is a valid measure of effectiveness in adverse weather. Under the same road lighting conditions, there is a difference in obstacle recognition distance according to weather conditions, and the obstacle recognition distance is longer in the order of normal > rain > fog; the difference is found to occur up to \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Weather**} & **Lighting Classes** & **Color Temperature** & **\(n\)** & **Mean** & **SD** & **\(t\)** & **\(p\)** \\ \hline \multirow{4}{*}{Normal} & M1 & 4940 K & 60 & 63.07 & 16.61 & \(-\)0.008 & 0.993 \\  & M1 & 3006 K & 60 & 63.08 & 16.37 & \(-\)0.008 & 0.993 \\ \cline{2-8}  & M3 & 4940 K & 60 & 55.89 & 15.16 & \multirow{2}{*}{1.240} & \multirow{2}{*}{0.220} \\  & M3 & 3006 K & 60 & 54.12 & 15.08 & \multirow{2}{*}{1.546} & \multirow{2}{*}{0.128} \\ \cline{2-8}  & M5 & 4940 K & 60 & 50.29 & 12.97 & \multirow{2}{*}{1.546} & \multirow{2}{*}{0.128} \\  & M5 & 3006 K & 60 & 48.73 & 14.69 & \multirow{2}{*}{1.546} & \multirow{2}{*}{0.128} \\ \hline \multirow{4}{*}{Fog} & M1 & 4940 K & 60 & 19.29 & 2.95 & \multirow{2}{*}{\(-\)3.826} & \multirow{2}{*}{\(<\)0.001} \\  & M1 & 3006 K & 60 & 20.63 & 3.39 & \(-\)3.826 & \multirow{2}{*}{\(<\)0.001} \\ \cline{2-8}  & M3 & 4940 K & 60 & 15.17 & 3.61 & \multirow{2}{*}{\(-\)12.360} & \multirow{2}{*}{\(<\)0.001} \\  & M5 & 3006 K & 60 & 19.38 & 3.36 & \(-\)12.360 & \multirow{2}{*}{\(<\)0.001} \\ \cline{2-8}  & M5 & 4940 K & 60 & 15.07 & 2.79 & \multirow{2}{*}{\(-\)6.751} & \multirow{2}{*}{\(<\)0.001} \\  & M1 & 3006 K & 60 & 17.58 & 4.09 & \(-\)6.751 & \multirow{2}{*}{\(<\)0.001} \\ \hline \multirow{4}{*}{Rain} & M1 & 4940 K & 60 & 34.53 & 7.03 & \multirow{2}{*}{\(-\)6.885} & \multirow{2}{*}{\(<\)0.001} \\  & M1 & 3006 K & 60 & 37.70 & 6.98 & \(-\)6.885 & \multirow{2}{*}{\(<\)0.001} \\ \cline{2-8}  & M3 & 4940 K & 60 & 31.40 & 5.34 & \multirow{2}{*}{\(-\)5.867} & \multirow{2}{*}{\(<\)0.001} \\  & M3006 K & 60 & 33.80 & 5.99 & \(-\)5.867 & \multirow{2}{*}{\(<\)0.001} \\ \cline{2-8}  & M5 & 4940 K & 60 & 30.07 & 5.04 & \multirow{2}{*}{\(<\)0.001} \\ \cline{2-8}  & M5 & 3006 K & 60 & 31.82 & 5.93 & \(-\)3.943 & \multirow{2}{*}{\(<\)0.001} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Significance of difference in obstacle recognition distance by color temperature. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Classification**} & \multicolumn{2}{c}{**Obstacle Recognition Distance Ratio Compared to 3006 K**} \\ \hline
**Weather** & \multicolumn{2}{c}{**Fog**} & \multicolumn{2}{c}{**Rain**} \\ \hline
**Color Temperature** & **3006 K** & **4940 K** & **3006 K** & **4940 K** \\ \hline \multirow{3}{*}{Lighting classes} & M1 & 100.0\% & 93.5\% & 100.0\% & 91.6\% \\  & M3 & 100.0\% & 78.3\% & 100.0\% & 92.9\% \\ \cline{1-1}  & M5 & 100.0\% & 85.7\% & 100.0\% & 94.5\% \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Obstacle recognition distance ratio compared to 3006 K.  
72.86%. Through these results, it was verified that performance evaluation of road lighting according to weather conditions is necessary. 2.