Human performance modeling for system of systems analytics: combat performance-shaping factors.

The US military has identified Human Performance Modeling (HPM) as a significant requirement and challenge of future systems modeling and analysis initiatives. To support this goal, Sandia National Laboratories (SNL) has undertaken a program of HPM as an integral augmentation to its system-of-system (SoS) analytics capabilities. The previous effort, reported in SAND2005-6569, evaluated the effects of soldier cognitive fatigue on SoS performance. The current effort began with a very broad survey of any performance-shaping factors (PSFs) that also might affect soldiers performance in combat situations. The work included consideration of three different approaches to cognition modeling and how appropriate they would be for application to SoS analytics. This bulk of this report categorizes 47 PSFs into three groups (internal, external, and task-related) and provides brief descriptions of how each affects combat performance, according to the literature. The PSFs were then assembled into a matrix with 22 representative military tasks and assigned one of four levels of estimated negative impact on task performance, based on the literature. Blank versions of the matrix were then sent to two ex-military subject-matter experts to be filled out based on their personal experiences. Data analysis was performed to identify the consensus most influential PSFs. Results indicate that combat-related injury, cognitive fatigue, inadequate training, physical fatigue, thirst, stress, poor perceptual processing, and presence of chemical agents are among the PSFs with the most negative impact on combat performance.

[1]  Arthur I. Siegel,et al.  Human Performance in Continuous Operations: Description of a Simulation Model and User's Manual for Evaluation of Performance Degradation , 1981 .

[2]  Susan G. Hill,et al.  Soldier Performance Issues in C2 `On the Move' , 2005 .

[3]  Debra J. Patton,et al.  Quantification of Cognitive Process Degradation While Mobile, Attributable to the Environmental Stressors Endurance, Vibration, and Noise , 1998 .

[4]  Gavriel Salvendy,et al.  Handbook of human factors. , 1987 .

[5]  I. Janis,et al.  Decision Making: A Psychological Analysis of Conflict, Choice, and Commitment , 1977 .

[6]  Shlomo H. Dover,et al.  The Characterization and Prediction of Soldier Performance During Routine Service and in Combat , 2002 .

[7]  W B Toscano,et al.  Effects of Command and Control Vehicle (C2V) operational environment on soldier health and performance. , 1999, Human performance in extreme environments : the journal of the Society for Human Performance in Extreme Environments.

[8]  R. Hogan Hogan Personality Inventory manual , 1986 .

[9]  Mikael Lundin,et al.  Simulating the effects of mental workload on tactical and operational performance in tankcrew , 2004 .

[10]  F. Ritter,et al.  Steps Towards Including Behavior Moderators in Human Performance Models in Synthetic Environments , 2000 .

[11]  Craig R Lawton,et al.  Human performance modeling for system of systems analytics :soldier fatigue. , 2005 .

[12]  Michael J. Griffin,et al.  Evidence of impaired learning during whole-body vibration , 1992 .

[13]  Richard W. Pew,et al.  Modeling human and organizational behavior : application to military simulations , 1998 .

[14]  Ken Parsons,et al.  Ergonomics assessment of thermal environments , 2005 .