Designing an Error Resolution Checklist for a Shared Manned-Unmanned Environment

Abstract

The role of unmanned vehicles in military and commercial environments continues to expand resulting in Shared Manned-Unmanned (SMU) domains. While the introduction of unmanned vehicles can have many benefits, humans operating within these environments must shift to high-level supervisory roles, which will require them to resolve system errors. Error resolution in current Human Supervisory Control (HSC) domains is performed using a checklist; the error is quickly identified, and then resolved using the steps outlined by the checklist. Background research into error resolution identified three attributes that impact the effectiveness of an error resolution checklist: domain predictability, sensor reliability, and time availability. These attributes were combined into a Checklist Attribute Model (CAM) demonstrating that HSC domains with high levels of complexity (e.g. SMU domains) are ill-suited to error resolution using traditional checklists. In particular, it was found that more support was required during such error identification, as data is uncertain and unreliable. A new error resolution checklist, termed the GUIDER (Graphical User Interface for Directed Error Recovery) Probabilistic Checklist, was developed to aid the human during the error identification process in SMU domains. Evaluation was performed through a human performance experiment requiring participants to resolve errors in a simulated SMU domain using the GUIDER Probabilistic Checklist and a traditional checklist tool. Thirty-six participants were recruited, and each was assigned to a single checklist tool condition. Participants completed three simulated error scenarios. The three scenarios had varying sensor reliability levels (low, medium, high) to gauge the impact of uncertainty on the usefulness of each checklist tool.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2010
Accession Number
ADA531511

Entities

People

  • Jacqueline M. Tappan

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • C4I
  • Human Systems
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Cognition
  • Cognitive Systems Engineering
  • Cognitive Workload
  • Commercial Aviation
  • Control Systems
  • Health Services
  • Human Factors Engineering
  • Human Supervisory Control
  • Information Processing
  • Information Science
  • Psychology
  • Reasoning
  • Systems Engineering
  • Unmanned Aerial Systems
  • Unmanned Aerial Vehicles
  • Unmanned Vehicles

Readers

  • Aviation Safety Risk Assessment.
  • Distributed Systems and Data Platform Development
  • Wetland-Land-Environmental Management.

Technology Areas

  • Autonomy
  • Autonomy - Human-Robot Interaction
  • Autonomy - UAVs