## 4 Results and Discussion
Remarkable among the national roads are the DN76 sector from Deva to Brad to Varfurile to Oradea, the DN1C sector from Baia Mare to Livada, and the DN18 sector from Sighetu Marmatiei to Baia Mare. Additionally, the county road DJ186 from Sacel to Vadu Izei is ranked in the high impact category. The second phase of the spatial analysis concentrates on modeling the cumulative impact of the five factor categories analyzed earlier: severity, mode of occurrence of traffic incidents, weather conditions, traffic restrictions, and the regulations induced by traffic \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & **Intersections** & \begin{tabular}{c} **Public Transport** \\ **Station** \\ \end{tabular} & \begin{tabular}{c} **Roadway** \\ **Alignment Signs** \\ \end{tabular} & \
\begin{tabular}{c} **Temporary** \\ **Traffic Signals** \\ \end{tabular} &
\begin{tabular}{c} **Railroad** \\ **Crossings** \\ \end{tabular} & **Weight** \\ \hline Intersections & 1 & 3 & 5 & 7 & 9 & 0.557 \\ \hline Public transport station & 1/3 & 1 & 2 & 5 & 7 & 0.208 \\ \hline Roadway alignment signs & 1/5 & 1/2 & 1 & 3 & 7 & 0.122 \\ \hline Temporary traffic signals & 1/7 & 1/5 & 1/3 & 1 & 3 & 0.067 \\ \hline Railroad crossings & 1/9 & 1/7 & 1/7 & 1/9 & 1 & 0.046 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: AHP score for factors related to traffic signal system. Figure 6: Spatial distribution of cumulative impact based on the influence of traffic sign regulations. signs. This analysis builds upon the aggregation of these factors, weighted according to their significance as determined by the implementation of the AHP matrix (Table 8). The application of the final AHP matrix and its incorporation into the spatial analysis model enables the determination of the overall aggregated impact of traffic incidents recorded in Romania. This approach also facilitates the identification of risks they induce in the territory. The matrix implementation underscores the significant contribution of incident severity, accounting for approximately 55.7%, which is notably higher compared to all other factors in the final analysis. Other factors like the mode of accident occurrence and meteorological conditions also hold substantial importance, with shares of 20.7% and 13.2%, respectively. This emphasizes their significant role both in the direct assessment of road accident casualties and in the economic repercussions of accident occurrences. Incidents arising from non-compliance with traffic restrictions and actions related to traffic signs hold less influence in the spatial analysis, contributing 6.6% and 4.8%, respectively. The quantitative assessment of the spatial distribution of cumulative impact was focused primarily on the medium-high to very high impact categories because the other two categories, while covering extensive areas, do not present a significant risk to the territory, largely due to the spatial configuration of Romania's road network. In this context, the medium-high impact category is particularly prominent, representing 61.6% of the total areas analyzed, followed by the high impact category at 37.7% and the very high impact category with a minimal percentage of 0.7%. Collectively, these percentages indicate a medium to high level of vulnerability across Romanian territory to road accidents. However, the relatively small percentage of the very high impact class should not be neglected. Despite its limited spatial coverage, this category represents a very high vulnerability and potential risk, as it is primarily identified within inner-village areas and as hotspots on main routes or sections with intense and congested traffic. Therefore, its influence in the overall assessment of the risk posed by traffic accidents in Romania is extremely significant and carries a high potential for adverse effects. In analyzing the spatial arrangement of the impact categories (Figure 7), the medium, high, and very high categories are notably prominent.