Using Simulation Models to Analyze the Effects of Crew Size and Crew Fatigue on the Control of Tactical Unmanned Aerial Vehicles (TUAVs)

Abstract

This report describes a study conducted by Micro Analysis and Design, Inc., for the U.S. Army Research Laboratory (ARL). One area of research examined by ARL was the staffing required to operate tactical unmanned aerial vehicles (TUAVs). The primary objective of the study was to use simulation modeling to analyze how fatigue, crew size, and rotation schedule affect operator workload and performance during the control of a TUAV. Computer simulation models were developed with the Micro Saint Discrete Event Simulation software to simulate the tasks that operators perform when controlling a TUAV. These models, which contain system-specific attributes of the Shadow 200 TUAV, included a fatigue function to predict performance effects for day and night missions. Subject matter experts (SMEs) provided the list of tasks involved in controlling a TUAV (during normal operations and emergencies), the order of these tasks, and the visual, auditory, cognitive, and psychomotor workload values associated with each task. Twelve different crew configurations were examined for the tactical operations center (TOC) and the launch and recovery station (LRS), which ranged in size from 8 to 15 crew members. The conclusions from executing the models and interviewing SMEs (during 12- and 18-hour missions) indicate that reducing the number of aerial vehicle operators (AVOs) and mission payload operators (MPOs) in the TOC can result in more aerial vehicle mishaps during emergencies, increased search time, and a decreased number of targets detected. For example, compared to six AVOs or MPOs in the TOC, the addition of two crew members resulted in only slight performance gains of a 6% increase in target detection and a 4% decrease in target search time. However, when the members of the crew were reduced to four AVOs or MPOs in the TOC, there was substantial performance loss (20% decrease in target detection and a 15% increase in target search time).

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2002
Accession Number
ADA405012

Entities

People

  • Brett A. Walters
  • Jon French
  • Michael J. Barnes
  • Shawn Huber

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Human Systems
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Cognitive Workload
  • Computer Simulations
  • Computers
  • Control Systems
  • Detection
  • Human Factors Engineering
  • Information Processing
  • Maintenance
  • Military Research
  • Mission Profiles
  • Simulations
  • Sleep Deprivation
  • Target Detection
  • Test And Evaluation
  • Unmanned Aerial Vehicles

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Circadian Sleep-Wake Regulation and Chronobiology
  • Computational Modeling and Simulation

Technology Areas

  • Autonomy