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Analysis reveals trends in safety-critical systems' mission abort policies, enhancing decision-making with artificial intelligence and risk assessment.
Background: Mission abort is a critical engineering practice aimed at preventing asset loss and ensuring mission success, especially under challenging operational conditions. Patents granted on safety-critical systems have significantly improved real-time risk assessment capabilities, enabling more precise triggering of mission abort, including aerospace, maritime, and autonomous systems. The ability to abort a mission can effectively distinguish between system safety and catastrophic failure. Objective: Research on mission abort policies seeks to balance maximizing mission success probability with minimizing the risk of system failure. This paper provides a comprehensive analysis of how mission abort strategies have evolved over time. Methods: We delved into the design principles of effective mission abort policies that can adapt to various system characteristics, mission requirements, and environmental variables. Furthermore, we explored methodologies employed in system performance metrics and policy optimization that enhance decision-making processes. Results: Through a review of existing methodologies, we identified opportunities for future improvement, such as the integration of artificial intelligence and predictive analytics. Discussion: Our analysis revealed key trends in strategy evolution and highlighted commonalities in effective design principles. These innovations can enable more robust and timely responses to mission risk, ultimately contributing to higher safety in mission-critical operations. Conclusion: The insights gained underscored the importance of mission abort policies in achieving the core objective of balancing mission success and system safety.
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Rongce Sun (2025) studied this question.
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