## 4 Engineering Example Validation
### Analysis of Results  
The data processing and calculations at all stages have screened out eight high-risk road sections of SC2 highway that are greatly affected by adverse meteorological conditions, accounting for about 19.05% of the non-tunnel road sections along the whole route. According to Table 4, when the road section has fog and snow adverse risk meteorological responsiveness, its value is significantly higher than the meteorological risk responsiveness under rainy day adverse meteorological conditions, indicating that at the macro level, the degree of influence of fog and snow adverse meteorology on road traffic safety is much higher than that of a rainy day. LD_18 and LD_43, which have the largest meteorological responsiveness in rainy days, and LD_45 and LD_49, which have the largest meteorological responsiveness in fog and snow, were selected for key analysis, and the risk responsiveness radar charts are shown in Figure 8.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Route Unit** & \begin{tabular}{c} **Rainy Weather Risk** \\ **Response/Ratio** \\ \end{tabular} & \
\begin{tabular}{c} **Foggy Weather Risk** \\ **Response/Ratio** \\ \end{tabular} &
\begin{tabular}{c} **Snowy Weather Risk** \\ **Response/Ratio** \\ \end{tabular} \\ \hline LD\_18 & 20.63\%/1.35 & 0.00\%/0.00 & 0.00\%/0.00 \\ LD\_19 & 3.75\%/1.42 & 0.00\%/0.00 & 0.00\%/0.00 \\ LD\_30 & 2.50\%/1.37 & 0.00\%/0.00 & 0.00\%/0.00 \\ LD\_31 & 2.50\%/1.53 & 0.00\%/0.00 & 0.00\%/0.00 \\ LD\_40 & 5.00\%/1.45 & 0.00\%/0.00 & 0.00\%/0.00 \\ LD\_43 & 19.38\%/1.64 & 0.00\%/0.00 & 0.00\%/0.00 \\ LD\_45 & 5.63\%/1.26 & 25.00\%/5.58 & 33.33\%/7.44 \\ LD\_49 & 4.38\%/1.19 & 0.00\%/0.00 & 66.67\%/18.17 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Accident-prone sections of SC2 highway under adverse weather conditions.  
Figure 7: Calculation results of meteorological risk response ratio of SC2.  
According to the results of Figure 8, the response of LD_18 and LD_43 road sections to the control group and the adverse meteorological risk in rainy days is much higher than that of other road sections. Referring to the level longitudinal line indexes of LD_18 and LD_43 in the level longitudinal data, the minimum radius of the level curve of LD_18 is 560 m, the maximum longitudinal slope is \(-3.34\%\), and the road section exists as an S-curve; the minimum radius of the level curve of LD_43 is 720 m, the maximum longitudinal slope is 3.50%, and the road section exists as an S-curve. The minimum radius of level curve of LD_18 is 560 m, the maximum longitudinal slope is \(-3.34\%\), and there is an S-shaped curve in the road section; the minimum radius of level curve of LD_43 is 720 m, and the maximum longitudinal slope is 3.50%. Both road sections have low level and longitudinal linear indexes, which is in line with the characteristics of accident-frequent road sections.  
The accident-prone road sections LD_45 and LD_49 under foggy and snowy adverse meteorological conditions have a much larger adverse meteorological risk response and response ratio than other road sections. Combined with the flat and longitudinal line of the two road sections, the minimum radius of the plane curve of the LD_45 road section is 551.15 m, and the maximum longitudinal slope is \(-1.80\%\); the minimum radius of the plane curve of the LD_49 road section is 560 m, and the maximum longitudinal slope is 3.78%. LD_45 section and LD_49 section plane line index in all the accident-prone sections in the lowest standard; at the same time, LD_45 section in the existence of downhill, combined with fog, snowy adverse meteorological conditions of the accident mechanism, in line with the theoretical logic. Combined with the above analysis, it can be concluded that LD_18, LD_43, LD_45, and LD_49 are the key accident-prone sections.