Risk assessment of the operations of maritime autonomous surface ships

Abstract

Maritime Autonomous Surface Ships (MASS) are attracting increasing attention in the maritime industry. Despite the expected benefits in reducing human error and significantly increasing the overall safety level, the development of autonomous ships would undoubtedly introduce new risks. The overall goal of this work is to develop an approach to evaluate the risk level of major hazards associated with MASS. To that extent, a Failure Modes and Effects Analysis (FMEA) method is used in conjunction with Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) to quantify the risk levels of the identified hazards. The results show that ‘interaction with manned vessels and detection of objects’ contributes the most to the overall risk of MASS operations, followed by ‘cyber-attacks’, ‘human error’ and ‘equipment failure’. The findings provide useful insights on the major hazards and can aid the overall safety assurance of MASS.