Authored by the Safety of Autonomous Systems Working Group (SASWG), and building on a previous edition, this document now provides a coherent set of objectives that should be satisfied by any compelling safety argument for an autonomous system.There is a deliberate focus on the novel safety assurance challenges that are associated with autonomy-enabling techniques, especially Artificial Intelligence (AI) developed using Machine Learning (ML) approaches. Consequently, this document is best employed within a wider Safety Management System (SMS).The objectives are organised into three frameworks, covering issues related to computations, autonomy architectures and platforms. Where possible, these frameworks and the associated objectives have been compared and contrasted to related documents. This provides some confidence that the listed objectives are representative of an emerging consensus of what is required to support autonomous system safety arguments. Nevertheless, the current edition represents a step on a journey. As further work is conducted, and experience is gained, revisions are expected. To support this, comments on this document are actively encouraged.In the previous edition, three frameworks were identified and of these the computational-level framework with projections and objectives was described. In this edition, the other two frameworks have been renamed and fully developed.
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