Current status of models for the human operator as a controller and decision maker in manned aerospace systems

The increased complexity of aerospace vehicles, with emphasis on automatic controls, has considerably altered the role of the human operator in such systems. Routine, burdensome tasks previously performed by man are now automated. As a result, the human task requires a greater emphasis on the monitoring and decision making aspects than on the control problem. Any attempt to automate these decision processes or to augment them for semi-automatic procedures must necessarily be based on a quantitative understanding of human capabilities in complex decision and control tasks. Considerable data are available on the information gathering and processing aspects of human behavior. From these results mathematical models of human decision processes and adaptive behavior have been proposed for specific control situations. In this paper we survey accepted techniques and models for analyzing and predicting human performance in complex multi-control and multidisplay situations commonly found in aerospace systems. The models that we consider have been developed or proposed for the related human functions of information processing, decision making and control. This paper discusses the relative advantages, disadvantages and limitations of each of the modeling schemes. Prospects for mechanizing all or part of the decision functions performed by human operators are considered - specific examples being in the automation of human failure detection and adaption to sudden changes in the system operating conditions.