Towards a Framework for Safety Assurance of Autonomous Systems

Autonomous systems have the potential to provide great benefit to society. However, they also pose problems for safety assurance, whether fully auton-omous or remotely operated (semi-autonomous). This paper discusses the challenges of safety assur-ance of autonomous systems and proposes a novel framework for safety assurance that, inter alia, uses machine learning to provide evidence for a system safety case and thus enables the safety case to be updated dynamically as system behaviour evolves.