Analysing Risk Influencing Factors for the Navigational Safety of Hazardous Cargo Vessels Using Bayesian Networks

Enhancing navigational safety of hazardous cargo vessels constitutes a critical imperative for sustaining maritime transportation system stability and fostering sustainable industry development. Based on the developed database containing 106 accident reports involving hazardous cargo vessels collected from the International Maritime Organization (IMO), this study aims to analyze the key risk influencing factors (RIFs) contributing to the maritime traffic accidents. Utilizing text analysis, the research first identifies critical RIFs across five primary domains, which are human, vessel, cargo, environment, and management. A Bayesian network model is subsequently developed to map out the interrelationships among these identified navigational safety RIFs. The findings suggest that factors such as