Tensions in stakeholder perspectives on blockchain technology in sustainable food system transformation

A periodically unattended bridge operation is a key focus in Maritime Autonomous Surface Ship (MASS) technologies. The German B ZERO project aims to develop capabilities for autonomous cargo ship navigation within a predefined operational envelope. This envelope includes thresholds for navigation, environment, ship state, and decision-making components. MASS technology must meet or exceed conventional safety standards. Thus, a safety assessment of B ZERO follows IMO Formal Safety Assessment guidelines, using the Bow-Tie Model for hazard identification and risk analysis. The approach emphasises quantitative methods like Fault and Event Tree Analysis, for risk comparison between attended and unattended bridge operations. The analysis incorporates literature-derived probabilities and risk control measure definitions based on two metrics: occurrence probability estimates and subgraph centrality scores. These are used separately and combined to identify high impact risks. Results show that effective risk control measures target nodes with both high occurrence probability and high subgraph centrality. Importantly, the subgraph centrality metric is useful when quantitative data is limited, allowing risk impact assessment based on logical relationships of risks. This approach integrates traditional probabilistic methods with network-based analysis, offering valuable insights for maritime autonomous systems across various data availability scenarios.