Construction of Risk Assessment Model for Maritime Autonomous Surface Ship Using Fuzzy Cognitive Map

Abstract

The rapid advancement and expanding applications of artificial intelligence (AI) are driving significant change across industries, prompting proactive adaptation and reform. Within the shipping industry, this has brought increased focus on the risk management implications of developing maritime autonomous surface ships (MASS). While highly autonomous MASS represent a major step forward in applying AI to shipping management and offer numerous potential benefits, they also introduce unique challenges. This study investigates the use of MASS with an AL5 autonomy level within bulk shipping companies. Through expert interviews, literature reviews, and questionnaire data analysis, it explores the relationships between various risk factors associated with MASS operations. Leveraging the SHELL model, fuzzy cognitive maps, and sensitivity analysis, the study develops a risk assessment model for MASS. Finally, it discusses management implications, acknowledges research limitations, and offers suggestions for the shipping industry regarding MASS implementation, while also providing guidance for future research into MASS operational regulations.