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Descriptive model of system development activities and man machine systems for determining optimal human performance in aerospace systems
Man-machine system simulation for flight vehicles
Man-machine system simulation for flight vehicles, discussing simulator complexity, realism and interrelation of feedback sensing cues
Quantitative evaluation of operator reliability in man-machine system
Effects of time delay in visual feedback loop of man-machine system
Theories and models conventionally employed to analyze man machine systems such as remotely manned vehicles and processes are reviewed. Basic ideas of supervisory or heirarchical manning, and needs for modeling are discussed.
A large proportion of the problems associated with complex systems have been attributed, at least in part, to the human operators, maintenance personnel, or managers who work within these systems. It appears, therefore, that improving man-machine system design may contribute to decreasing substantially the frequency of problems in complex systems. In this paper, alternative views of how the design of man-machine systems might be improved are described and contrasted. A two-part approach for achieving the desired improvements is proposed.
Simulation, models, and games as analogies measurement criteria in man-machine system simulation
Human performance prediction in man machine systems - test catalog tables
Path optimization for numerically controlled remote manipulator - man-machine system
Tests and test techniques for human performance prediction in man-machine systems tasks
Selected and annotated bibliography of human performance prediction in man machine systems - Vol. 3
Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.
SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.
The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.
Man-machine performance measurements
Method for system synthesis of higher order, man machine control loops
A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also 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.