Many useful mathematical models for manual control, monitoring, and decision-making tasks in man-machine systems have been designed and successfully applied. However, critical comments have occasionally been made, mainly by practitioners concerned with the design of complex man-machine systems. They especially blame models which seem to explain only data from abstract subtask experiments designed particularly for these models.
In this review paper, an initial approach to bridging the gap between these two perspectives of models is presented. From the manifold of possible human tasks, a very popular baseline scenario has been chosen, namely car driving. A hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a timesharing computer analogy.
The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in real complex tasks. Also, other mathematical tools so far not often applied to man-machine systems are discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued.
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