Employing Field Monitoring and Runtime Safety Verification for Cumulative Operational Safety Assurance in a SafetyDevOps Process

Operational safety assurance for autonomous and highly automated systems is imperative due to the inherent complexities and dynamic operational environments these systems encounter. As autonomous systems evolve, ensuring their safety throughout their life-cycle becomes indispensable, not just during the deployment but also during operation. Safety assurance has evolved from traditional document-based approaches to more structured, model-driven methodologies to enhance clarity and traceability. This evolution has been driven by the need for more rigorous, repeatable, and scalable processes to ensure safety in increasingly complex systems. Traditional safety assurance methods do not adequately address the dynamic real-time challenges and changes an autonomous system might face, necessitating a more adaptive and continuous approach. This paper highlights the need for a Cumulative Operational Safety Assurance approach addressing multiple research gaps. The cumulative aspect of the approach ensures that the safety assurance case evolves continuously and incrementally with operational data, improving decision-making and system safety.