Simulation and HSI

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A soldier tests out a heavy-wheeled-vehicle driver simulator. (Image courtesy of the Department of Defense.)

A soldier tests out a heavy-wheeled-vehicle driver simulator. (Image courtesy of the Department of Defense.)

Previous discussions on our blog that reference “simulation” have been in the context of repeating the same process, algorithm, or heuristic with different inputs. This type of simulation is very helpful in demonstrating the variability of a problem and the pathways its execution can take. Ultimately, simulation provides insight into uncertainty of the results, preferring a confidence interval in place of a point estimate. In this aspect, ADS has significant capabilities in model development, execution, and analysis.

Another facet of “simulation,” leans more towards presenting an artificial environment, often visually and perhaps in a virtual reality (VR). Generation of the environment is subject to significant computational demands and, as the expectation for realism increases, can easily be too time-consuming to be accomplished in real-time. High-fidelity simulators of this fashion are used extensively in high-performance disciplines where the actual vehicle or training is too expensive or high-risk. Examples include high-speed racing (e.g., NASCAR), commercial and military aviation, other military vehicles, even simulator-based training for dismounted troops in urban battlefields.

How does this type of simulation apply to ADS and how could it be used? Continuing with the examples above, ADS, by precisely measuring the eye scan rate of the operators (pilots, drivers, etc.) and performing extensive analysis, we can evaluate the operator’s performance and potential for improvement. More so, after analyzing the behaviors and habits of highly-experienced operators, we can use that material to show less experienced operators improved habits and techniques in real-time as they use the simulator. This capitalizes on mimicry or adaptation to accelerate their development and improvement, reducing a process that may normally take many years into a shorter time period; in effect steepening the learning curve.

In addition to nurturing new drivers and pilots, these methods also apply to the introduction of new systems to both senior and junior operators. This reduces the time to evaluate new systems, incorporate them into the vehicle cockpit or dash, and provide not just post-event but also real-time feedback to the operators and trainers on scan rates and impacts on performance.

ADS has four simulation/design experts, two of which are aviation subject matter experts.  We have extensive leadership experience advancing Modeling and Simulation in new application domains such as human-machine interfaces, autonomy, and healthcare. Our four experienced analysts have multiple military simulation experiences, so we are able to link our flight experience to other simulation applications.
movie The Age of Adaline 2015

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