An Analysis System Relating Individual Human Performance Measures to Overall Mission Effectiveness

Abstract

When applied in acquisition the goal of modeling and simulation is to support technology decisions. Both constructive and virtual simulations produce great quantities of data. The information derived from these data, if obtained in a clear and timely manner, can provide acquisition professionals with insight into critical issues surrounding development and selection of new technologies. Currently, however, the derivation process is expensive, time-consuming and often unreliable. The intent of the CART data visualization effort is to improve this process by developing a suite of applications addressing critical aspects of an overall solution to the problem of translating simulation data to technology acquisition decisions. Our experience has shown that 3 levels of analysis are required to thoroughly understand the results provided by a CART simulation: specifying effects of technology alternatives on mission performance, tracing effects of human performance on mission performance and conducting detailed analysis of why failures occurred. Research addressing the first two levels is currently being conducted. Our approach in this research is embodied in the development of 6 applications: a test plan description application that serves as a simulation design database for raw data, an abstraction hierarchy application that links lower levels of human performance to high-level mission outcomes, a data repository application that allows description of data file contents in terms of elements critical to required acquisition decisions, a performance measure definition application that allows users to define performance measures at level of the abstraction hierarchy, a performance measure computation application that automates performance measure calculation, and a diagnostic hierarchy exploration application that allows analysts to trace low-level performance effects to mission outcomes in ways enabling comparisons across test conditions.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA430257

Entities

People

  • Bryan E. Brett
  • Christopher R. Hale
  • Jeffrey A. Doyal

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Air Force Research Laboratories
  • Application Software
  • Cognitive Systems Engineering
  • Complex Systems
  • Computations
  • Data Analysis
  • Data Visualization
  • Engineers
  • Hierarchies
  • Military Research
  • Motor Skills
  • Operating Systems
  • Storage
  • Systems Engineering
  • Visualizations

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Database Systems and Applications
  • Defense Acquisition Program Management