Autonomous Maritime Systems Safety and Risk Analysis
Summary
Autonomous maritime systems comprise a spectrum of vessels ranging from remotely operated unmanned platforms to fully autonomous surface ships. Safety and risk analysis for these systems encompasses evaluation of navigational reliability, system resilience to human error and environmental hazards, and regulatory frameworks required for safe integration. Modern approaches blend data-driven risk modelling, system-theoretic hazard analysis and human-factor assessments to address challenges unique to automation at sea. Automated control algorithms must contend with dynamic marine environments, where situational awareness relies heavily on sensor fusion and real-time data streams such as Automatic Identification System inputs. Risk factors extend beyond collision and grounding to include cyber-security threats, sensor failures and unforeseen interactions within socio-technical networks. System-theoretic methods support identification of control failures and emergent hazards throughout the design lifecycle, while probabilistic models offer quantifiable metrics for accident likelihood and consequence severity. The global significance of this research lies in its potential to reduce human casualties, optimise fuel efficiency and advance sustainable shipping. Practical applications are seen in pilot projects deploying autonomous vessels in controlled waterways, evolving certification standards and adaptive legal frameworks for unmanned operations.
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Autonomous Maritime Systems Safety and Risk Analysis publication trend
The graph below shows the total number of articles in autonomous maritime systems safety and risk analysis across all publications each year (not limited to Nature Index journals).
Technical terms
Maritime Autonomous Surface Ship (MASS): Vessel capable of operating without onboard human intervention through automated control systems and advanced sensors.
Bayesian network: Probabilistic graphical model representing interdependencies among risk factors for maritime accidents and enabling scenario-based prediction.
Human-centred design: Approach that prioritises seafarer interaction, skills and organisational structures in the development and deployment of autonomous vessels.
Automatic Identification System (AIS): Real-time tracking network for vessel position, course and speed, fundamental to collision risk assessment and traffic analysis.
System-Theoretic Process Analysis (STPA): Method for identifying hazardous control interactions in complex systems by modelling hierarchical control structures and feedback loops.
References
- Data-driven Bayesian network for risk analysis of global maritime accidents. Reliability Engineering & System Safety (2023).
- A human-centred review on maritime autonomous surfaces ships: impacts, responses, and future directions. Transport Reviews (2024).
- Graph-based ship traffic partitioning for intelligent maritime surveillance in complex port waters. Expert Systems with Applications (2023).
- A framework to model the STPA hierarchical control structure of an autonomous ship. Safety Science (2020).
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