An intelligent Fusion Framework for Risk Assessment of Autonomous Ship through Functional Mapping Criterion Sub-Intervals into Single Interval Method

Abstract

Nowadays, intelligent information technology can implement high-level information processing and decision-making activities that can support risk assessment of autonomous. Risk assessment is a critical process for deploying autonomous ships, ensuring these innovative vessels' safe and efficient operation. There is a need to identify, analyze, and mitigate potential risks associated with system reliability, collision avoidance, cybersecurity, environmental conditions, human interaction, regulatory compliance, sensor performance, data integrity, emergency response, and testing and validation. This work provides an overview of the essential considerations and objectives of risk assessment in autonomous boats. We used the multi-criteria decision-making model to deal with various criteria. The Ranking of Alternatives through Functional Mapping Criterion Sub-Intervals into Single Interval (RAFSI) method is applied to rank the alternatives. We used the ten criteria and twenty options in this study. The results show that the proposed framework can provide a comprehensive risk assessment framework that can enable stakeholders to gain insights into potential hazards and vulnerabilities unique to autonomous ships.