Human Memory Limitations in Multi-Object Tracking.

Abstract

Basic perofrmance data were obtained on the effect of critical task variables in unaided multi-object tracking behavior. Six observers viewed computer-generated displays in which five, seven, or nine objects represented targets that moved in random linear trajectories at one of two speeds. Displayed positions were updated six times at intervals of 5, 8, 13 or 18 seconds, and no track history was provided. The task for the observer was to monitor the trajectories and then predict the next position of each object. Results showed that the unaided observer can keep track of up to about seven moving objects. Performance improved as the interval between updates was increased to about 13 seconds. These variables interact in their effects on tracking performance and may be trade off in a complex manner. A family of mathematical models of human memory that focus on the encoding, learning, and rehearsal processes of the observer was developed. Two of the models' predictions were consistent with the data observed and those reported in the psychological literature. The analysis of human memory and information processing limitations should be extended to more complex operational tasks to support system designers with quantitative estimates of operator performance. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1982
Accession Number
ADA117586

Entities

People

  • Frank L. Greitzer
  • Ramon L. Hershman
  • Richard T. Kelly

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Coding
  • Command And Control
  • Computers
  • Control Systems
  • Electronics
  • Information Processing
  • Learning
  • Mathematical Models
  • Measurement
  • Mental Processes
  • Military Research
  • Models
  • Motor Skills
  • Psychology
  • Statistical Sampling
  • Trajectories

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation
  • Sensor Fusion and Tracking Systems.