An Information-Based Approach for System Autonomy Metrics Part I: Metrics Definition

In many real world aerospace applications, system Autonomy is the most single significant and meaningful attribute of an Intelligent Autonomous System IAS. This paper proposes performance metrics for IAS, which are related to the main dimensions of Autonomy. Metrics are presented and defined. The metrics reflects the most meaningful characteristics of system Autonomy. The approach taken in this paper defines system or agent autonomy with respect to its self-capability to accomplish its assigned mission goals while operating under uncertain unexpected dynamic environment, uncertain dynamic scenario or self-faulty situations, and without or with very little intervention of a human operator or an external agent, throughout the mission cycle. The metrics enables to classify the system autonomy level, according to the sensitivity of the system performance to relative changes in autonomy related entities. The metrics are based on a comprehensive approach. It does not consider the Autonomy level at each phase of the sense-aware-decide-act process, separately. The proposed metrics are quantitative, relative, and based on concepts from Information theory as well as from Control and Systems theory. Using the System Autonomy Metrics, the system designer can compare between competitive designs, architectures, computational paradigms or, algorithms, as related to the desired system performance, with respect to Autonomy. These metrics are currently being used in an on-going research, development and engineering work.