Modeling workload impact in multiple unmanned vehicle supervisory control
Name
Donmez-2010-Modeling Workload Impact in Multiple Unmanned.pdf
Size
850.54 KB
Format
Adobe PDF
Checksum (MD5)
c9393e2bbd73b19539ed417de15cfd26
Author(s) • •
Donmez, Birsen
Nehme, Carl E.
Cummings, M. L.
Date Issued
November 2010
Journal
Proceedings of the IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans
Publisher
Institute of Electrical and Electronics Engineers
Citation
Donmez, B., C. Nehme, and M.L. Cummings. “Modeling Workload Impact in Multiple Unmanned Vehicle Supervisory Control.” Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions On 40.6 (2010) : 1180-1190. © 2010 IEEE.
Version
Final published version
Abstract
Discrete-event simulations for futuristic unmanned vehicle (UV) systems enable a cost- and time-effective methodology for evaluating various autonomy and human-automation design parameters. Operator mental workload is an important factor to consider in such models. We suggest that the effects of operator workload on system performance can be modeled in such a simulation environment through a quantitative relation between operator attention and utilization, i.e., operator busy time used as a surrogate real-time workload measure. To validate our model, a heterogeneous UV simulation experiment was conducted with 74 participants. Performance-based measures of attention switching delays were incorporated in the discrete-event simulation model by UV wait times due to operator attention inefficiencies (WTAIs). Experimental results showed that WTAI is significantly associated with operator utilization (UT) such that high UT levels correspond to higher wait times. The inclusion of this empirical UT-WTAI relation in the discrete-event simulation model of multiple UV supervisory control resulted in more accurate replications of data, as well as more accurate predictions for alternative UV team structures. These results have implications for the design of future human-UV systems, as well as more general multiple task supervisory control models.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TSMCA.2010.2046731