Risk Evaluation of Maritime Autonomous Surface Ship Operations: A Formal Safety Assessment Approach

Abstract

Maritime autonomous surface ships (MASSs) are reshaping the organization of navigation, ship operation, remote control and maritime supervision. However, the transition from crewed navigation to autonomy also changes the structure of safety risk. Traditional ship risk assessment approaches rely heavily on historical accident records and crew-centered operational assumptions, whereas MASS operations involve coupled risks arising from perception systems, autonomous decision-making, communication links, cybersecurity, remote control centers, environmental uncertainty and management readiness. To address the scarcity of operational accident data and the need for a structured safety evaluation method, this paper develops a Formal Safety Assessment (FSA)-based risk evaluation framework for MASS operations. A hierarchical indicator system is established from five dimensions: ship machinery, human factors, environmental factors, information technology and management. A frequency-severity risk criterion is then constructed by defining the Frequency Index (FI), Severity Index (SI) and Risk Index (RI), and by introducing the ALARP principle to classify unacceptable, tolerable and broadly acceptable risk regions. On this basis, an integrated fuzzy analytic hierarchy process is proposed to determine factor weights, transform expert judgements into membership degrees, and calculate comprehensive risk scores. A case study using 50 expert questionnaires shows that the overall risk score of MASS operation is 5.64, located in the ALARP region. Among the first-level indicators, environmental factors, information technology factors and ship machinery factors present relatively high risk levels, with scores of 6.82, 6.60 and 6.25, respectively. At the secondary-indicator level, intelligent navigation system, weather conditions, hydrometeorological conditions, communication capability, equipment and systems, navigation decision-making, and environmental perception are identified as high-intensity risk indicators. Further contribution decomposition reveals that environmental perception, routine ship management, navigation decision-making, and communication capability contribute most substantially to the overall risk profile due to their higher systemic importance. The proposed framework provides an interpretable approach for MASS safety assessment and risk-control prioritization under limited operational data availability.