Review of Dynamic Risk Assessment Methods for Navigation Safety of Ro‐Pax Vessels

Abstract Dynamic Risk Assessment (DRA) which could be based on various methods might be key component to improve the navigation safety of the vessel. This paper is focused on review of various DRA methodologies applicable to Ro‐Pax vessels. A literature review examined different key DRA techniques, including Fuzzy Logic, Bayesian Networks, Real‐time Data Analytics, Machine Learning, IoT and Situational Awareness, evaluating their ability to manage support decision‐making model. The integration of advanced techniques enhances the accuracy and responsiveness of risk assessments. Fuzzy Logic allows to effectively manage imprecise data, while Bayesian Networks enable dynamic updates based on real‐time inputs. Machine Learning improves operational efficiency by predicting threats from navigational data patterns. Continuous evolution and integration of different DRA methods can significantly improve safety of navigation for all types of vessels. Adopting these approaches helps ship's operators enhance risk assessment. Future research should focus on developing hybrid models that combine multiple DRA techniques to enhance decision‐making in navigation safety.