# A Novel Methodology for Planning Urban Road Safety Interventions
## 5 Conclusions  
Road safety remains a critical priority for urban administrations, requiring data-driven strategies to reduce accidents and optimize resource allocation. This study introduced an integrated methodology that combines reactive accident analysis with proactive risk assessment, leveraging the iRAP star rating system and Geographic Information Systems (GIS) to improve road safety planning. By incorporating cost-benefit analysis (CBA), this approach not only identifies high-risk areas but also prioritizes interventions based on their expected safety benefits and economic feasibility. A key contribution of this research is its ability to bridge the gap between historical crash data analysis and proactive risk evaluation, offering a more comprehensive decision-making framework than traditional black-spot identification methods. Unlike previous studies that rely solely on past accident records or predictive models, this methodology proactively addresses infrastructure-related risks, even in locations with limited historical data. Additionally, the integration of CBA within the iRAP framework represents a novel advancement, ensuring that safety investments are both impactful and cost-efficient. Despite its strengths, integrating reactive and proactive approaches posed challenges. Methodological conflicts arose in cases where historical crash data did not align with proactive risk assessments--for example, some locations flagged as high-risk by iRAP had \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{3}{*}{**[\(\ell\)/Year]**} & \multicolumn{2}{c}{**Critical Point A**} & \multicolumn{4}{c}{**Critical Point B**} \\  & **Benefit** & **SC\({}_{saved}\)** & **Int. Cost** & **B/C** & **[\(\ell\)/Year]** & **Benefit** & **Int. Cost** & **B/C** \\ \hline Option 1 & 1,494,068.31 & 22,211.39 & 67.26 & Option 1 & 352,703.28 & 6659.63 & 52.96 \\ Option 2 & 1,179,748.45 & 9116.14 & 129.41 & Option 2 & 183,623.96 & 3780.00 & 48.57 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: B/C ratio for critical points A and B. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**[\(\ell\)/Year]** &
\begin{tabular}{c} **Priority** \\ **Intervention** \\ \end{tabular} & **Benefit \(\textit{SC}_{saved}\)** & **Int. Cost** & **B/C** \\ \hline Critical point A & Option 2 & 1,179,748.45 & 9116.14 & 129.41 \\ Critical point B & Option 1 & 352,703.28 & 6659.63 & 52.96 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Prioritization of interventions, network wide. relatively low recorded accident frequencies. To settle these differences, field inspections and local traffic flow analyses were conducted, ensuring that interventions addressed both recorded incidents and underlying infrastructure risks. Another challenge involved data compatibility, as municipal and ISTAT datasets exhibited discrepancies in accident reporting. These were mitigated through geolocation standardization and cross-verification to improve data reliability. This study supports Vision Zero goals by providing a proactive, data-driven framework that identifies risk areas before severe crashes occur. Unlike traditional reactive approaches that focus solely on black spots, the integrated methodology prioritizes preventative measures, such as redesigning roads to inherently reduce conflict points and crash severity. The inclusion of CBA further strengthens Vision Zero efforts by ensuring cost-effective interventions that maximize safety gains. The proposed methodology aligns with both Italian and EU road safety policies, particularly EU's Strategic Road Safety Action Plan (2021-2030), which promotes data-driven risk assessment and network-wide road safety evaluations, and Italy's National Road Safety Plan (PNSS 2030), which prioritizes high-risk site interventions and encourages cost-effective infrastructure improvements.