A Quantitative Measure for Shared and Complementary Situation Awareness

Abstract

As team structures evolve and become more complex, with human and automated agents working together to accomplish team goals, measurement approaches for system situation awareness must also adapt. This paper proposes a novel approach to the measurement of SA for human automation teams. Limitations of existing individual SA measurement approaches are highlighted with a particular focus on the sensitivity of current measures to knowledge held across human and automated agents in complex sociotechnical systems. We propose that elements from team communication data can be used as a basis for the quantification of shared and complementary situation awareness. We present a conceptual measurement approach for using communication data to measure shared and complementary situation awareness for human-automation teams, appropriate for both open or closed loop communication. This paper discusses how such a measurement approach would be applied specifically for human-automation teams, including automation that functions as decision aids, as managers, and automation that learns with the human operator, and discusses implications of our measure for training and design.