Predicting controller capacity in supervisory control of multiple UAVs
In the future vision of allowing a single operator to remotely control multiple unmanned vehicles, it is not well understood what cognitive constraints limit the number of vehicles and related tasks that a single operator can manage. This paper illustrates that, when predicting the number of unmanned aerial vehicles (UAVs) that a single operator can control, it is important to model the sources of wait times (WTs) caused by human-vehicle interaction, particularly since these times could potentially lead to a system failure. Specifically, these sources of vehicle WTs include cognitive reorientation and interaction WT (WTI), queues for multiple-vehicle interactions, and loss of situation awareness (SA) WTs. When WTs were included, predictions using a multiple homogeneous and independent UAV simulation dropped by up to 67%, with a loss of SA as the primary source of WT delays. Moreover, this paper demonstrated that even in a highly automated management-by-exception system, which should alleviate queuing and WTIs, operator capacity is still affected by the SA WT, causing a 36% decrease over the capacity model with no WT included. © 2008 IEEE.
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- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
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- 09 Engineering
- 08 Information and Computing Sciences
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
- 40 Engineering
- 09 Engineering
- 08 Information and Computing Sciences