The Human Dimension of Closing the Training Gap for Fifth-Generation Fighters

Based on a review of the recent technical literature there is little question that a serious training gap exists for fifth-generation fighters, primarily arising from the need to provide their own red-air. There are several methods for reducing this gap, including injecting virtual and constructive threats into the live cockpit. This live-virtual-constructive (LVC) training approach provides a cost effective means for addressing training needs but faces several challenges. Technical challenges include data links and information assurance. A more serious challenge may be the human factors dimension of representing virtual and constructive entities in the cockpit while ensuring safety-of-flight. This also needs to happen without increasing pilot workload. This paper discusses the methods Rockwell Collins and the University of Iowa's Operator Performance Lab use to assess pilot workload and training fidelity measures in an LVC training environment and the research we are conducting in safety-of-flight requirements of integrated LVC symbology

Combinatorial Gelfand Models

A combinatorial construction of Gelfand models for the symmetric group, for its Iwahori-Hecke algebra and for the hyperoctahedral group is presented

Physiological Based Simulator Fidelity Design Guidance

The evolution of the role of flight simulation has reinforced assumptions in aviation that the degree of realism in a simulation system directly correlates to the training benefit, i.e., more fidelity is always better. The construct of fidelity has several dimensions, including physical fidelity, functional fidelity, and cognitive fidelity. Interaction of different fidelity dimensions has an impact on trainee immersion, presence, and transfer of training. This paper discusses research results of a recent study that investigated if physiological-based methods could be used to determine the required level of simulator fidelity. Pilots performed a relatively complex flight task consisting of mission task elements of various levels of difficulty in a fixed base flight simulator and a real fighter jet trainer aircraft. Flight runs were performed using one forward visual channel of 40 deg. field of view for the lowest level of fidelity, 120 deg. field of view for the middle level of fidelity, and unrestricted field of view and full dynamic acceleration in the real airplane. Neuro-cognitive and physiological measures were collected under these conditions using the Cognitive Avionics Tool Set (CATS) and nonlinear closed form models for workload prediction were generated based on these data for the various mission task elements. One finding of the work described herein is that simple heart rate is a relatively good predictor of cognitive workload, even for short tasks with dynamic changes in cognitive loading. Additionally, we found that models that used a wide range of physiological and neuro-cognitive measures can further boost the accuracy of the workload prediction