Modeling workload impact in multiple unmanned vehicle supervisory control
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 ope...
| Main Authors: | , , |
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2011
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| Online Access: | http://hdl.handle.net/1721.1/65349 |
| _version_ | 1811081870686814208 |
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| author | Donmez, Birsen Nehme, Carl E. Cummings, M. L. |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Donmez, Birsen Nehme, Carl E. Cummings, M. L. |
| author_sort | Donmez, Birsen |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T11:53:43Z |
| format | Article |
| id | mit-1721.1/65349 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:53:43Z |
| publishDate | 2011 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/653492022-10-01T06:45:03Z Modeling workload impact in multiple unmanned vehicle supervisory control Donmez, Birsen Nehme, Carl E. Cummings, M. L. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Cummings, M. L. Cummings, M. L. 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. Charles River Analytics (Firm) United States. Office of Naval Research 2011-08-23T14:43:30Z 2011-08-23T14:43:30Z 2010-11 2009-07 Article http://purl.org/eprint/type/JournalArticle 1083-4427 INSPEC Accession Number: 11588420 http://hdl.handle.net/1721.1/65349 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. en_US http://dx.doi.org/10.1109/TSMCA.2010.2046731 Proceedings of the IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 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. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Donmez, Birsen Nehme, Carl E. Cummings, M. L. Modeling workload impact in multiple unmanned vehicle supervisory control |
| title | Modeling workload impact in multiple unmanned vehicle supervisory control |
| title_full | Modeling workload impact in multiple unmanned vehicle supervisory control |
| title_fullStr | Modeling workload impact in multiple unmanned vehicle supervisory control |
| title_full_unstemmed | Modeling workload impact in multiple unmanned vehicle supervisory control |
| title_short | Modeling workload impact in multiple unmanned vehicle supervisory control |
| title_sort | modeling workload impact in multiple unmanned vehicle supervisory control |
| url | http://hdl.handle.net/1721.1/65349 |
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