Human performance modeling for system of systems analytics :soldier fatigue.

The military has identified Human Performance Modeling (HPM) as a significant requirement and challenge of future systems modeling and analysis initiatives as can be seen in the Department of Defense's (DoD) Defense Modeling and Simulation Office's (DMSO) Master Plan (DoD 5000.59-P 1995). To this goal, the military is currently spending millions of dollars on programs devoted to HPM in various military contexts. Examples include the Human Performance Modeling Integration (HPMI) program within the Air Force Research Laboratory, which focuses on integrating HPMs with constructive models of systems (e.g. cockpit simulations) and the Navy's Human Performance Center (HPC) established in September 2003. Nearly all of these initiatives focus on the interface between humans and a single system. This is insufficient in the era of highly complex network centric SoS. This report presents research and development in the area of HPM in a system-of-systems (SoS). Specifically, this report addresses modeling soldier fatigue and the potential impacts soldier fatigue can have on SoS performance.

[1]  D. Dinges,et al.  Summary of the key features of seven biomathematical models of human fatigue and performance. , 2004, Aviation, space, and environmental medicine.

[2]  D Dawson,et al.  A quantitative model of work-related fatigue: background and definition , 2001, Ergonomics.

[3]  Comparison of Mathematical Model Predictions to Experimental Data of Fatigue and Performance , 2004 .

[4]  Qiang Ji,et al.  Non-Intrusive Real Time Human Fatigue Modelling and Monitoring , 2003 .

[5]  U. Trutschel,et al.  Circadian alertness simulator for fatigue risk assessment in transportation: application to reduce frequency and severity of truck accidents. , 2004, Aviation, space, and environmental medicine.

[6]  Qiang Ji,et al.  Information fusion with Bayesian networks for monitoring human fatigue , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[7]  Adam Fletcher,et al.  Prediction of Performance during Sleep Deprivation and Alcohol Intoxication using a Quantitative Model of Work-Related Fatigue , 2003 .

[8]  Gary Klein,et al.  The effect of acute stressors on decision making. , 1996 .

[9]  Hans P A Van Dongen.  Comparison of mathematical model predictions to experimental data of fatigue and performance. , 2004, Aviation, space, and environmental medicine.

[10]  D. Dawson,et al.  A quantitative model of work-related fatigue: empirical evaluations , 2001, Ergonomics.

[11]  R. Guttkuhn,et al.  Human fatigue risk simulations in 24/7 operations , 2003, Proceedings of the 2003 Winter Simulation Conference, 2003..