Assessing Accident Rates and Frequency of Incidents Involving Dangerous Goods in the Genoa District at Sub-regional Scale - a Data-driven Approach

Abstract

The transport of Dangerous Goods (DG) in Italy occurs mainly via road networks as part of supply chain logistics. Although they account for a relatively small proportion of overall freight, accidents involving DG can have significant consequences and are classified as Low Probability High Consequence (LPHC) events. These events, although rare, present considerable risks for both the environment and the public, particularly in the face of the increase in industrial disasters. This paper presents a data-driven analysis aimed at quantifying the rates and frequencies of accidents associated with the transport of DG in the Genoa district. Using a deterministic risk approach, the study identifies the least DG transport routes and assesses risk levels accordingly. The integration of the Internet of Things (IoT) and Information and Communication Technologies (ICT) allows real-time monitoring of the transport of DG, enabling the identification of accident frequencies within defined spatial and temporal parameters. Using ICT tools and the database of National Fire and Rescue Service (NFRS), accidents involving trucks transporting DG are identified and analyzed. The study highlights the importance of rapid and effective emergency response processes to minimize individual damage and mitigate environmental and property damage. This research provides valuable information for risk assessment and emergency response planning in the Genoa district and highlights the importance of taking advantage of data-driven approaches to improve DG transport safety.