## 4 Results and Discussion  
The spatial consolidation of databases, achieved through network analysis implementation, enables the assessment of road traffic incident risks. This is based on the integration of individual factors, such as the impact of incident types in relation to distance. These factors collectively contribute to defining the risk, while considering their varying levels of influence and significance in the broader context of understanding road traffic incidents. To analyze the datasets, the Multi Criteria Decision Analysis (MCDA) technique, specifically the Analytic Hierarchy Process (AHP) method, was selected. Given the substantial number of databases involved in the analysis, totaling 23, and the need to eliminate subjectivity and redundancy, a decision was made to integrate these databases in two primary steps. The initial step requires conducting an integration analysis using the AHP method on databases with distinct characteristics, leading to the development of a spatial database that delineates the impact they generate. These databases were categorized into five major groups based on their characteristics: severity, mode of occurrence, weather conditions, traffic restrictions, and the influence of traffic signs on incident occurrences. This analysis involves implementing and examining the statistical coefficients of the matrices to determine the specific weights and importance of each factor. Subsequently, these weights are applied in the GIS environment for spatialization, resulting in five consolidated and unified outcomes. The analysis of the spatial impact related to the severity of traffic incidents was conducted by implementing a matrix (Table 3), which is structured around various factors: very severe incidents, severe incidents, incidents of moderate severity, and minor incidents. The results from applying the matrix show two main findings. First, the matrix's consistency is established at 6%, suggesting that the determination of factor importance is accurately executed. Second, the substantial influence of'very severe' and'severe' incidents is evident, constituting approximately 62% for the former and 22% for the latter in the overall result. In contrast,'moderate severity' and'minor' incidents hold a smaller role in assessing the spatial impact, together accounting for about 16%. This reduced significance inversely correlates with the prevalence of these incident types in Romania. The spatial pattern of the cumulative impact of road traffic incidents (Figure 2), based on their severity, predominantly aligns with European roads and the areas immediately surrounding urban centers adjacent to these road categories. A notable absence of major impact is observed on most national roads, despite them being common sites for traffic incidents. This is attributed to the pronounced influence of very severe and severe incidents in the spatial analysis, which are more frequent on European road categories. Particularly prominent is the E60 European road, especially the Ploiesti-Brasov sector, known for its heavy traffic. Also with high levels are E85 in Eastern Romania, specifically the Ramnicu Sarat-Bacau sector, and E70 in Western Romania, in the Mehadia-Timisoara sector, both characterized by high levels of vehicle traffic, with the latter noted for a significant presence \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **Very Severe** & **Severe** & **Moderate** & **Minor** & **Weight** \\  & **Incident** & **Incident** & **Incident** & **Incident** & **Weight** \\ \hline Very severe incident & 1 & 3 & 7 & 9 & 0.628 \\ \hline Severe incident & 1/3 & 1 & 3 & 7 & 0.226 \\ \hline Moderate incident & 1/7 & 1/3 & 1 & 3 & 0.090 \\ \hline Minor incident & 1/9 & 1/7 & 1/3 & 1 & 0.057 \\ \hline Lambda = 4160; CI = 0.053; CR = 0.059; Consistence = 6\%. & & & \\ \end{tabular}
\end{table} 
Table 3: AHP score for incident severity factors. of heavy traffic vehicles. The study also identifies high-impact areas in terms of severity around most large urban centers in Romania.