PSI - Issue 84

Giuseppe Alessandro Battista et al. / Procedia Structural Integrity 84 (2026) 694–701

698

4. ANSFISA prioritization criteria in public oversight The supervisory function exercised by ANSFISA represents the operational cornerstone for ensuring systemic safety across the Italian road and highway networks, acting as a superior control mechanism over the activities of individual operators (Garusi et al., 2024). The core of this activity lies in the Annual Program of Supervisory Activities, a strategic planning tool that defines intervention priorities based on a rigorous analysis of the risk profiles of different operators and infrastructure sections. The introduction of Decree Law 77/2021, known as the Simplifications Decree, marked a fundamental evolution in the relationship between the Agency and managing entities, clarifying competencies and strengthening audit powers over Safety Management Systems (SMS). This new regulatory framework requires ANSFISA to select sections for inspection not only based on temporal rotation criteria but through the use of performance and risk indicators that allow for the identification of latent criticalities before they transform into overt failures. The adoption of advanced multi-criteria decision-making techniques, such as the integrated SWARA and MARCOS approach, enables the Agency to assess road safety in contexts characterized by high uncertainty, ensuring that inspection resources are allocated where the potential for risk reduction is greatest (Jafarzadeh Ghoushchi et al., 2023). In this context, oversight shifts from mere documentary control to field verification and systemic auditing, integrating data from asset censuses with the results of visual inspections and the attention classes of bridges and galleries defined by the managers themselves. 5. European benchmarking and safety management models Comparing national practices with international best practices and the models adopted by peer Safety Agencies in Europe is an essential element for validating and updating Italian prioritization criteria. Analyzing the continental landscape reveals that many leading nations in the transport sector have implemented monitoring systems based on predictive algorithms and the full digitalization of assets. In countries such as Germany or France, the integration of computer-aided resilience simulation tools allows for the analysis of disaster scenarios and the prediction of infrastructure behavior under extreme stress, providing vital data for emergency planning (Li et al., 2025). Furthermore, European benchmarking highlights the importance of aligning infrastructure management with global sustainable development goals, promoting models that are not limited to structural stability but also consider environmental impact and service continuity within urban communities. The analysis of annual reports from entities such as the ETSC (European Transport Safety Council, 2025) and EuroRAP (International Road Assessment Programme, 2025) reveals that the effectiveness of national safety systems depends on the ability to centralize information in interoperable platforms, similar to the Italian AINOP system, where every infrastructure component is monitored throughout its entire life cycle. This holistic approach allows for the transfer of cross-asset budget management models, where resources are distributed according to a global risk ranking that spans bridges, tunnels, and pavements, thereby optimizing public spending and maximizing the level of safety experienced by road users. 6. Methodological proposal for the prioritization of interventions Based on the criticalities identified in the analysis of the national system and the suggestions derived from international benchmarking, this research proposes a comprehensive methodology aimed at supporting prioritization choices in both institutional and operational spheres. This framework is based on the integration of four key indicators: risk, severity, exposure, and impact, designed to be fully compatible with existing asset management systems and the requirements of Safety Management Systems (SMS). The effectiveness of this methodology depends crucially on the quality of the collected data and the adoption of rigorous pre-processing strategies, which are necessary to ensure that infrastructure performance forecasts are accurate and free from bias, especially when employing data-driven forecasting models (Wang et al., 2025). The proposed approach moves beyond traditional deterministic models, which often fail to capture the complex, non-linear deterioration mechanisms inherent in real-world conditions, suggesting instead the use of stochastic-based performance models to better handle the uncertainties of infrastructure aging (Shahid et al., 2025).