Qualitative Risk Assessment Methodology for Maritime Autonomous Surface Ships: Cognitive Model-Based Functional Analysis and Hazard Identification

Abstract

Maritime Autonomous Surface Ships (MASSs) incorporate advanced digital technologies, thus rendering their systems more complex and diverse than those of conventional ships. Furthermore, the operation of MASSs, which introduces new risks not encountered in conventional ship operations, differs significantly from that of conventional manned vessels. These challenges highlight the necessity for a more systematic and structured approach to risk analysis and control. This study presents a qualitative risk assessment methodology to identify and manage hazardous scenarios associated with MASS operations systematically. The key feature of the proposed methodology is the integration of cognitive model-based functional analysis with the widely adopted hazard identification (HAZID) method, which enables a structured and comprehensive analysis process. Functional analysis is used to examine the functions required for MASS operations and to analyze interconnected systems to fulfill these functions. Subsequently, HAZID is performed to identify hazardous scenarios that may cause functional degradation or failure. To illustrate the proposed methodology, a case study is presented based on a qualitative risk assessment conducted in preparation for the field trial of an Autonomous Navigation System. Practical applications, including the presented case study, demonstrated the effectiveness of this methodology as a systematic tool for identifying and evaluating potentially hazards in MASS operations.