Autonomous systems must integrate well with individuals and with society at large. Such systems often integrate into—and form collectively into—an autonomous ecosystem. That ecosystem—the connections and interactions between autonomous systems, over networks, with the physical environment, and with humans—must be assured, resilient, productive, and fair in the autonomous future.
Systems engineering is critical for ensuring the operational success for which the autonomous systems were intended. The full systems engineering life cycle must be addressed in the context of autonomous systems, including concept, context, requirements, design, integration, operationalization, verification and validation, testing and evaluation, and maintenance. Hardware, software, and algorithms must sustain the intended processing workload and data storage needs under a variety of conditions. Communications between systems and their interoperability must be engineered to support highly dynamic interactions and enable cooperation and teaming across multiple systems and human supervisors. The technology must be architected for resiliency, extensibility, and evolution as increasing levels of autonomy place new demands on underlying infrastructures. New systems engineering approaches must be developed to manage the unprecedented level of interactions between autonomous platforms in an assured, autonomous ecosystem.
Human-system interaction must provide people with an understanding of an autonomous system’s decisions and actions, the ability to interact at appropriate levels of abstraction, and the ability to override the system’s actions. New human-system engineering techniques are needed to ensure autonomous systems will be smoothly and readily adopted into society.