An Analysis of Decision Making Strategies Used By P-3 Pilots in Hazardous Situations

Abstract

Effective decision making in aeronautical environments, which often involves high elements of risk, is critical to mission success. Unfortunately, no proven methodology exists to train pilots to make successful decisions. Cockpit decision making has relied on traditional analytical models and methodologies that underestimate the role of pilot experience, expertise and judgement Naturalistic Decision Making models (NDM) contend that decision makers facing real-world decisions use experience and judgement to make timely decisions without analyzing a multitude of alternatives. This thesis analyzes 438 P-3 aviation hazard reports (hazreps) to ascertain which cognitive strategies from either the analytical or naturalistic methodology are more appropriate for handling malfunctions situations. The author presents a hybrid model of decision making by P-3 pilots based on the results of the analysis and strategies from both methodologies. This thesis recommends that decision making training be treated as a core activity of pilots not only in flight school, but alter qualification is complete. Training pilots to become experts will improve situational awareness and reduce the number of unfavorable outcomes in hazardous situations.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA376768

Entities

People

  • Christopher J. Watt

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Accidents
  • Aircrafts
  • Cognition
  • Command And Control
  • Decision Support Systems
  • Doctrine
  • Education
  • Engineers
  • Failure Mode And Effect Analysis
  • Hazards
  • Information Processing
  • Information Systems
  • Judgment
  • Psychology
  • Situational Awareness
  • Training
  • Warning Systems

Readers

  • Aviation Science / Aeronautics.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.