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Predictive Model for Human-Unmanned Vehicle Systems

Author(s)
Crandall, Jacob W.; Cummings, M. L.; Nehme, Carl E.
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Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/
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Abstract
Advances in automation are making it possible for a single operator to control multiple unmanned vehicles. However, the complex nature of these teams presents a difficult and exciting challenge for designers of human–unmanned vehicle systems. To build such systems effectively, models must be developed that describe the behavior of the human–unmanned vehicle team and that predict how alterations in team composition and system design will affect the system’s overall performance. In this paper, we present a method for modeling human–unmanned vehicle systems consisting of a single operator and multiple independent unmanned vehicles. Via a case study, we demonstrate that the resulting models provide an accurate description of observed human-unmanned vehicle systems. Additionally, we demonstrate that the models can be used to predict how changes in the human-unmanned vehicle interface and the unmanned vehicles’ autonomy alter the system’s performance.
Date issued
2009-11
URI
http://hdl.handle.net/1721.1/81769
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Journal
Journal of Aerospace Computing, Information, and Communication
Publisher
American Institute of Aeronautics and Astronautics
Citation
Crandall, Jacob W., M. L. Cummings, and Carl E. Nehme. “Predictive Model for Human-Unmanned Vehicle Systems.” Journal of Aerospace Computing, Information, and Communication 6, no. 11 (November 2009): 585-603.
Version: Author's final manuscript
ISSN
1542-9423

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