Advertisement

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

  • Willi Stein

Abstract

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.

Keywords

Human Operator Failure Detection Supervisory Control Independent Decision Optimal Control Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baron, S. (1984). A Control Theoretic Approach to Modelling Human Supervisory Control of Dynamic Systems. In: W.B. Rouse (Ed.). Advances in Man-Maschine Systems Research. Greenwich, Conn.: JAI Press.Google Scholar
  2. Carbonell, J.R. (1966). A Queueing Model of Many-Instrument Visual Sampling. IEEE Trans. Human Factors in Electron., Vol. 7, No. 4, p. 157–164.MathSciNetCrossRefGoogle Scholar
  3. Carbonell, J.R., Ward, J.L., and Senders, J.W. (1968). A Queueing Model of Visual Sampling Experimental Validation. IEEE Trans. Human Factors in Electron., Vol. 9, No. 3, p. 82–87.Google Scholar
  4. Clement, W.F., McRuer, D.T., and Klein, R.H. (1972). Systematic Manual Control Display Design. Proceedings, Guidance and Control Displays, CP-96. Neuilly sur Seine, France: AGARD.Google Scholar
  5. Curry, R.E., Kleinman, D.L., and Hoffman, W.C. (1977). A Design Procedure for Control/Display Systems. Human Factors, Vol. 19, No. 5, p. 421–436.Google Scholar
  6. Fitts, P.M., Jones, R.E., and Milton, J.L. (1950). Eye movements of aircraft pilots during instrument landing approaches. Aeronautical Engineering Review, Vol. 9, p. 1–5.Google Scholar
  7. Freund, L.E., and Sadosky, T.L. (1967). Linear Programming Applied to Optimization of Instrument Panel and Workplace Layout. Human Factors, Vol. 9, No. 4, p. 295–300.Google Scholar
  8. Gai, E.G., and Curry, R.E. (1976). A Model of the Human Observer in Failure Detection Tasks. IEEE Trans. Syst., Man, and Cybern., Vol. 6, No. 2, p. 85–94.zbMATHGoogle Scholar
  9. Gould, J.D. (1968). Visual Factors in the Design of Computer-Controlled CRT Displays. Human Factors, Vol. 10, No. 4, p. 359–376.Google Scholar
  10. Jones, J.C. (1981). Design Methods. Chichester, UK: John Wiley.Google Scholar
  11. Kleinman, D.L., and Curry, R.E. (1977). Some New Control Theoretic Models of Human Operator Display Monitoring. IEEE Trans. Syst., Man, and Cybem., Vol. 7, No. 11, p. 778–784.zbMATHCrossRefGoogle Scholar
  12. Kok, J., and van Wijk, R. (1978). Evaluation of Models Describing Human Operator Control of Slowly Responding Complex Systems. Delft, Netherlands: Delft University Press.Google Scholar
  13. Levison, W.H. (1971). A Control-Theory Model for Human Decision Making. Seventh Annual Conf. Manual Control, NASA SP-281. Washington, D.C.: National Aeronautics and Space Administration.Google Scholar
  14. Moray, N. (1985). Monitoring Behavior and Supervisory Control. In: K.R. Boff, L. Kaufman, J.-P. Thomas (Eds.), Handbook of Perception and Human Performance. New York: John Wiley.Google Scholar
  15. Nadler, G. (1985). Systems Methodology and Design. IEEE Trans. Syst., Man, and Cybern., Vol. 15, No. 6, p. 685–697.CrossRefGoogle Scholar
  16. Pattipati,K.R., Kleinman, D.L., and Ephrath, A.R. (1983). A Dynamic Decision Model of Human Task Selection Performance. IEEE Trans. Syst., Man, and Cybern., Vol. 13, No. 3, p. 145–166.Google Scholar
  17. Pau, L.F. (1981). Failure Diagnosis and Performance Monitoring. New York: Marcel Dekker.zbMATHGoogle Scholar
  18. Pew,R.W., Baron, S.,Feehrer, C. E., and Miller, D.C. (1977). Critical Review and Analysis of Performance Models Applicable to Man-Machine Systems Evaluation. BBN Report 3446. Cambridge, Mass.: BBN Laboratories.Google Scholar
  19. Pew, R.W., and Baron, S. (1983). Perspectives on Human Performance Modelling. Automatica, Vol. 19, No. 6, p. 663–676.CrossRefGoogle Scholar
  20. Phatak, A.V., and Kleinman, D.L. (1972). Current status of models for the human operator as a controller and decision maker in manned aerospace systems. Proceedings, Automation in Manned Aerospace Systems, CP-114. Neuilly-sur-Seine, France: AGARD.Google Scholar
  21. Rasmussen, J., and Rouse, W.B. (1981). Human Detection and Diagnosis of System Failures. New York: Plenum Press.CrossRefGoogle Scholar
  22. Rouse, W.B. (1980). Systems Engineering Models of Human-Machine Interaction. New York: North Holland.Google Scholar
  23. Rouse, W.B. (1981). Human-Computer Interaction in the Control of Dynamic Systems. Computing Surveys, Vol. 13, No. 1, p. 71–99.MathSciNetCrossRefGoogle Scholar
  24. Rouse, W.B., and Boff, K.R. (Eds.)(1987). System Design - Psychological Aspects. New York: North-Holland.Google Scholar
  25. Sage, A.P., and Melsa, J.L. (1971). Estimation Theory with Applications to Communications and Control. New York: McGraw-Hill.zbMATHGoogle Scholar
  26. Schrenk, L.P. (1969). Aiding the Decision Maker: A Decision Process Model. Ergonomics, Vol. 12, p. 543–557.CrossRefGoogle Scholar
  27. Senders, J.W. (1964). The Human Operator as a Monitor and Controller of Multidegree of Freedom Systems. IEEE Trans. Human Factors in Electron., Vol. 5, No. 1, p. 2–5.CrossRefGoogle Scholar
  28. Senders, J.W. (1983). Visual Scanning Processes. Tilburg, Netherlands: Tilburg University Press.Google Scholar
  29. Sheridan, T.B. (1970). On how often the supervisor should sample. IEEE Trans. S yst., Sci., and Cybern., Vol. 6, p. 140–145.zbMATHGoogle Scholar
  30. Sheridan, T.B., and Ferrell, W.R. (1974). Man-Machine Systems: Information, Control, and Decision Models of Human Performance. Cambridge: The MIT Press.Google Scholar
  31. Sheridan, T.B., and Johannsen, G. (Eds.)(1976). Monitoring Behavior and Supervisory Control. New York: Plenum Press.Google Scholar
  32. Sheridan, T.B. (1987). Supervisory Control. In: G. Salvendy (Ed.). Handbook of Human Factors. New York: John Wiley.Google Scholar
  33. Smallwood, R.D. (1967). Internal Models and the Human Instrument Monitor. IEEE Trans. Human Factors in Electron., Vol. 8, No. 3, p. 181–187.CrossRefGoogle Scholar
  34. Srinath, M.D., and Rajasekaran, R.K. (1979). An Introduction to Statistical Signal Processing with Applications. New York: John Wiley.Google Scholar
  35. Stein, W. (1981): A Monitoring and Decision Making Paradigm: Experiments and Human Operator Modelling. Proceedings, First European Annual Conference on Human Decision Making and Manual Control. Laboratory for Measurement and Control. University of Technology, Delft, The Netherlands.Google Scholar
  36. Stein, W., and Wewerinke, P.H. (1983). Human Display Monitoring and Failure Detection: Control Theoretic Models and Experiments. Automatica, Vol. 19, No. 6, p. 711–718.zbMATHCrossRefGoogle Scholar
  37. Tulga, M.K., and Sheridan, T.B. (1980). Dynamic Decisions and Work Load in Multitask Supervisory Control. IEEE Trans. Systems, Man, and Cybern., Vol. 10, No. 5, p. 217–232.CrossRefGoogle Scholar
  38. Wewerinke, P.H. (1976). Human control and monitoring - models and experiments. Proceedings, 12th Ann. Conf. Manual Control. Springfield, Virg.: National Technical Information Service.Google Scholar
  39. Wewerinke, P.H. (1983): Model of the Human Observer and Decision Maker–Theory and Validation. Automatica, Vol. 19, No. 6, p. 693–696.CrossRefGoogle Scholar
  40. Wierwille, W.W. (1981). Statistical Techniques for Instrument Panel Arrangement. In: J. Moraal, and K.-F. Kraiss (Eds.). Manned Systems Design. New York: Plenum Press.Google Scholar

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

Personalised recommendations