Models of Human Monitoring and Decision Making in Vehicle and Process Control

  • Willi Stein


The growing interest in monitoring and decision making and the related models depends on many factors. Due to increasing automation and the use of advanced information technology, the human’s function in vehicle and process control is shifting from a direct and continuously active involvement towards a supervisory control structure, where man-machine interaction is exercised through the mediation of a computer. Supervisory control indicates a hierarchy or coordinated set of human activities that includes initiating, monitoring, detecting events, recognizing, diagnosing, adjusting, and optimizing processes in systems that are otherwise automatically controlled. Thus, the spectrum of monitoring and decision making includes primary task components of the human operator in vehicle and process control. In this paper, a survey of models and related experimental studies of human monitoring and decision making is presented. Fitts et al. (1950) started with the empirical study of monitoring and Senders (1964) pioneered in the related model development (Moray, 1986). Special emphasis is given to the control theory models of monitoring and decision making which are based on the information processing structure of the optimal control model (OCM) developed by Kleinman, Baron, and Levison (see Baron (1984), Rouse (1980), and Sheridan and Ferrell (1974)). The experimental studies presented include a variety of multivariable monitoring and decision making tasks. Characteristic factors are, for example, the number of displayed dynamic processes, bandwidths, event probabilities and correlation among abnormal events and unfailed processes. The models predict several measures of monitoring and decision making behaviour, the decision speed/accuracy trade-off and the attentional characteristics, including the time requirements of effective instrument fixations and eye movements. Most of the predictions are based on a few free model parameters only. The considerable level of overall agreement between the models and the experimental results provides the predictive potential for the analysis, design, and evaluation of man-machine interfaces.


Human Operator Failure Detection Supervisory Control Independent Decision Optimal Control Model 
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Copyright information

© Springer Science+Business Media New York 1989

Authors and Affiliations

  • Willi Stein
    • 1
  1. 1.Research Institute for Human Engineering (FAT)Wachtberg-WerthhovenFederal Republic of Germany

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