Modeling of Helicopter Pilot Misperception During Overland Navigation

Abstract

This thesis provides a framework to model human belief and misperception in helicopter overland navigation. Helicopter overland navigation is a challenging mission area because it is a complex cognitive task, and failing to recognize when the aircraft is off-course can lead to operational failures and mishaps. A human-in-the-loop experiment to investigate pilot misperception during simulated overland navigation by analyzing actual navigation trajectory, pilots' perceived location, and corresponding confidence levels was designed. Fifteen military officers with prior overland navigation experience completed four simulated low-level navigation routes, two of which entailed autonavigation. Analysis shows that there is not a negative correlation between perceived and actual location of the aircraft, inferring that confidence is not a good indicator of performance. However, there is some evidence of a negative correlation between perceived location and intended route of flight, suggesting that there is a bias towards that intended flight route. If aviation personnel can proactively identify the circumstances in which misperception usually occurs in navigation, they may reduce mission failure and mishap rate. This study can help fleet squadrons and instructional commands improve operations that require low-level flight as well as crew resource management.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2012
Accession Number
ADA560584

Entities

People

  • Bradley T. Cowden

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Altimeters
  • Altitude
  • Aviation Personnel
  • Cognitive Workload
  • Collision Avoidance
  • Dead Reckoning
  • Flight Training
  • Global Positioning Systems
  • Navigation
  • Navigational Equipment
  • Navigators
  • Operations Research
  • Perception
  • Simulations
  • Students
  • Training

Readers

  • Aviation Science / Aeronautics.
  • Inertial Navigation Systems.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference