Operator State Estimation for Adaptive Aiding in Uninhabited Combat Air Vehicles

Abstract

This research demonstrated the first closed-loop implementation of adaptive automation using operator functional state in an operationally relevant environment. In the Uninhabited Combat Air Vehicle (UCAV) environment, operators can become cognitively overloaded and their performance may decrease during mission critical events. This research demonstrates an unprecedented closed-loop system, one that adaptively aids UCAV operators based on their cognitive functional state A series of experiments were conducted to 1) determine the best classifiers for estimating operator functional state, 2) determine if physiological measures can be used to develop multiple cognitive models based on information processing demands and task type, 3) determine the salient psychophysiological measures in operator functional state, and 4) demonstrate the benefits of intelligent adaptive aiding using operator functional state. Aiding the operator actually improved performance and increased mission effectiveness by 67%