TECRA: C2 application of adaptive automation theory - de Visser, Ewart J; LeGoullon, Melanie; Horvath, Don; Weltman, Gershon; Freedy, Amos; Durlach, Paula; Parasuraman, Raja (2010 IEEE Aerospace Conference, 2010)
This paper describes the design and initial positive evaluation of a prototype adaptive automation system to create an enhanced command and control (C2) infrastructure for more effective operation of unmanned vehicles. Our main project objective is to apply recent advances in cognitive engineering and display automation to create Technology for Enhanced Command and Control of Small Robotic Assets (TECRA). The initial goal is an enhanced C2 system for small unmanned aircraft vehicles (SUAVs). Our approach is to use adaptive display technology to improve shared situation awareness between the SUAV Commander and the SUAV Operator, to provide new channels of Commander-Operator communication, and to reduce Commander workload. At the core of our approach is a tri-modal adaptive interface display which involves adaptive information presentation in order to balance workload and to promote effective humansystem performance. This novel design came about as a direct result of field observations during a full-scale military exercise and a cognitive task analysis (CTA) based on these observations. Using the CTA, we designed the basic Commander's adaptive interface format and automated triggering methods. A priori GOMS analysis predicted a 50% decrease in time on task, based on a subset of representative tasks. Data collection to date supports these predictions. Furthermore, feedback from subject matter experts and comparisons between user performance on TECRA versus an existing SUAV platform suggests that TECRA is easier to use, quicker to learn, and provides more capabilities to the user than current systems. These results demonstrate how the TECRA application driven by a cognitive analysis of the Commander's task, by a mission model of the anticipated Commander's needs, and by mission templates and real-time robotic data has been able to validate theories of human-automation interaction in realworld domains such as unmanned aviation and military command and control.