Situation Awareness for Autonomous Agents

Situation Awareness is a prominent concept in the human factors community. It is used to analyze and eliminate common sources of human errors in complex tasks and has seen wide-spread use in many fields, such as aviation, health care or ergonomics. Humans who are situation aware are able to reliably generate competent performance, a skill that is also highly desired for other autonomous agents. Yet, the concept has seen only limited use in robotics. We attest this to a lack of clear definitions which would allow assessing an artificial agents capacity for Situation Awareness. Our major contribution is an application-agnostic definition of the terminology and the processes involved in acquiring Situation Awareness. By integrating our definitions into the perception-action-cycle we provide a connection to the agent's observable behavior. Our second major contribution is a way to estimate, whether an agent has lost Situation Awareness based on surprise. This measure can be used online and does not require explicit or implicit knowledge of the task. We evaluate our concept on a physical workspace built for abstract Human-Robot-Cooperation scenarios.