Human Information Processing and Supervisory Control.

Abstract

Although there are several well developed models of man as a manual controller, there is at present no general theory of supervisory control. However, with increasing use of microprocessors and automatic machinery the role of human operator is increasingly one of supervision rather than control, at least as long as the controller processes remain within the acceptable tolerances of normal performance. The design of complex automatic systems which must be supervised by a human operator should benefit from considering the particular properties of man as an information processor which are likely to render supervisory control a difficult task. This is especially true due to the fact that while for long periods he may be required to do little other than observe the system, he must nonetheless extract enough information about the state variables to enable him to make adequate decisions, and exercise adequate control, if emergency situations develop. This paper is an introduction to the empirical literature most relevant to matching the properties of the human operator to those of the machine when designing systems to be run under supervisory control. The literature citations are not intended to be exhaustive, but to be sufficient to establish the most important points which will be made. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1980
Accession Number
ADA092840

Entities

People

  • Neville Moray

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Air Traffic
  • Air Traffic Control Systems
  • Aircrafts
  • Cognition
  • Cognitive Workload
  • Control Systems
  • Databases
  • Detection
  • Human Factors Engineering
  • Human-Machine Systems
  • Information Processing
  • Information Science
  • Motor Skills
  • Psychology
  • Servomechanisms
  • Supervisory Control

Readers

  • Instructional Design and Training Evaluation.
  • Robotics and Automation.
  • Systems Analysis and Design