Improving road safety is a major challenge for urban administrations due to the high frequency of accidents and their associated social costs. This study presents a methodology that combines historical accident data analysis with a proactive risk assessment approach to enhance decision-making in road safety planning. Using the International Road Assessment Programme (iRAP) and Geographic Information Systems (GIS), the proposed framework identifies high-risk locations and estimates the benefits of planned safety interventions. A key innovation of this methodology is the integration of cost–benefit analysis to prioritize interventions, ensuring optimal resource allocation. The approach was tested in a medium-sized Italian city where it helped identify critical areas and assess the potential impact of various safety measures, such as intersection redesign and traffic-calming strategies. The results demonstrated a significant potential to reduce accidents and associated social costs, offering a scalable model for urban road safety planning. By integrating data-driven insights with proactive evaluation, this methodology supports urban administrations in implementing effective, targeted interventions that contribute to Vision Zero goals.
A Novel Methodology for Planning Urban Road Safety Interventions
E. Toraldo;N. Novati;M. Ketabdari
2025-01-01
Abstract
Improving road safety is a major challenge for urban administrations due to the high frequency of accidents and their associated social costs. This study presents a methodology that combines historical accident data analysis with a proactive risk assessment approach to enhance decision-making in road safety planning. Using the International Road Assessment Programme (iRAP) and Geographic Information Systems (GIS), the proposed framework identifies high-risk locations and estimates the benefits of planned safety interventions. A key innovation of this methodology is the integration of cost–benefit analysis to prioritize interventions, ensuring optimal resource allocation. The approach was tested in a medium-sized Italian city where it helped identify critical areas and assess the potential impact of various safety measures, such as intersection redesign and traffic-calming strategies. The results demonstrated a significant potential to reduce accidents and associated social costs, offering a scalable model for urban road safety planning. By integrating data-driven insights with proactive evaluation, this methodology supports urban administrations in implementing effective, targeted interventions that contribute to Vision Zero goals.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


