Documents / Report
This Defense Intelligence Reference Document, dated 15 December 2010, is a Defense Intelligence Agency report from its Advanced Aerospace Weapons System Applications (AAWSA) Program. It looks at how many unmanned spacecraft one human pilot could control during future deep-space missions, drawing on research into air traffic control and piloting of multiple unmanned vehicles. It concludes that the limits are about 16 craft for simple tasks, 7 for moderately complex tasks and 4 for complex mixed fleets. It adds that physiological measures can signal when an operator is overloaded.
“Sanderson”1 page
UNCLASSIFIED/ ,'F811. 8FFll!l*L 1!1!11! t!IIU:!Y 36 Loft, S., Sanderson, P., Neal, A. & Mooij, M. Modeling and predicting mental workload in en route air traffic control: critical review and broader implications. Hum Factors 49, 376-399 (2007). 37 Hendy, K. C., Liao, J. & Milgram, P. Combining time and intensity effects in assessing operator information-processing load. Hum Factors 39, 30-47 (1997). 38 Boone, J. 0. Toward the development of a new aptitude selection test battery for air traffic control specialists. Aviat Space Environ Med 51, 694-699 (1980). 39 Cohen, D., Wherry, R. J., Jr. & Glenn, F. Analysis of workload predictions generated by multiple resource theory. Aviat Space Environ Med 67, 139-145 ( 1996 ). 40 Hancock, P.A. & Szalma, J. L. Performance under stress. (Ashgate Pub., 2008). 41 Iani, C. & Wickens, C. D. Factors affecting task management in aviation. Hum Factors 49, 16-24 (2007). 42 Wickens, C. & Colcombe, A. Dual-task performance consequences of imperfect alerting associated with a cockpit display of traffic information. Hum Factors 49, 839-850 (2007). 43 Lansdown, T. C., Brook-Carter, N. & Kersloot, T. Distraction from multiple in- vehicle secondary tasks: vehicle performance and mental workload implications. Ergonomics 47, 91-104, doi:10.1080/00140130310001629775 (2004). 44 Pack, D. J., Delima, P., Toussaint, G. J. & York, G. Cooperative control of UAVs for localization of intermittently emitting mobile targets. IEEE Trans Syst Man Cybern B Cybern 39, 959-970, doi:10.1109/TSMCB.2008.2010865 (2009). 45 Wang, J., Qu, Z. H., Ihlefeld, C. M. & Hull, R. A. A control-design-based solution to robotic ecology: Autonomy of achieving cooperative behavior from a high- level astronaut command. Autonomous Robots 20, 97-112, doi:10.1007/s10514- 006-5942-5 (2006). 46 Dixon, S. R., Wickens, C. D. & Chang, D. Mission control of multiple unmanned aerial vehicles: a workload analysis. Hum Factors 47, 479-487 (2005). 47 Lee, J. H., Lee, B. H. & Choi, M. H. A real-time traffic control scheme of multiple AGV systems for collision free minimum time motion: A routing table approach. Ieee Transactions on Systems Man and Cybernetics Part a-Systems and Humans 28, 347-358 (1998). 48 Rouse, W. B. Systems engineering models of human-machine interaction. (North Holland, 1980). 49 Cummings, M. L. & Guerlain, S. Developing operator capacity estimates for supervisory control of autonomous vehicles. Human Factors 49, 1-15 (2007). 50 Kornguth, S. E., Steinberg, R. & Matthews, M. D. Neurocognitive and physiological factors during high-tempo operations. (Ashgate, 2010). 51 Cummings, M. L. & Mitchell, P. J. Predicting controller capacity in supervisory control of multiple UAVs. Jeee Transactions on Systems Man and Cybernetics Part a-Systems and Humans 38, 451-460, doi: 10.1109/tsmca.2007 .914757 (2008). 52 Cummings, M. L., Clare, A. & Hart, C. The Role of Human-Automation Consensus in Multiple Unmanned Vehicle Scheduling. Human Factors 52, 17-27, doi: 10.1177/0018720810368674 (2010). 26 UNCLASSIFIED//f81il err1e1At USE 014[1
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Report, from the dia collection. The PDF is mirrored here; the original link is above. 31 pages are in the text index: search them above, or from the library's search.