Human Operator Decision-Making in Manual Control

Abstract
To decide whether or not to attempt a given maneuver, an operator must consider the likelihood of his success as well as the costs or values of the possible outcomes. Detecting the future success of a maneuver from the physical circumstances that make it more or less difficult to achieve and from past experience is formally like detecting signals in noise. Two experiments are described, which indicate that the basic decision model and ROC analysis used for signal detection can also be applied to manual control decisions. Results are given comparing the decision performance of operators who execute the maneuvers with the performance of observers who only watch them.

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