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Proceedings Paper

Simulating human vehicle identification performance with infrared imagery and augmented reality assistance
Author(s): John J. Graybeal; Rachel T. T. Nguyen; Todd W. Du Bosq
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Paper Abstract

The U.S. Army CCDC C5ISR Night Vision and Electronic Sensors Directorate is researching the use of augmented reality (AR) technologies to improve the situational awareness and decision-making capabilities of EO/IR sensor operators. A major research requirement for such technologies involves defining the accuracy of AR information required to improve human performance for tasks related to EO/IR sensors, as AR systems may unintentionally provide inaccurate information to operators, which may be worse than providing no information at all. We designed a simulation to assess human performance during a vehicle identification task (using infrared imagery) when the operator receives aid via an AR system. U.S. Soldiers, trained to identify vehicles using infrared sensors, viewed images of the vehicles at different ranges in blocks while a simulated AR system attempted to identify each vehicle. Each block of images possessed an inherent level of AR accuracy (either 100%, 75%, or 50%). Performance with AR was compared to baseline performance (i.e., completing the task with no AR assistance). We further explored human performance by examining time-constrained decisions with AR. While perfect AR information was generally used effectively by participants, AR mistakes progressively increased human errors and slowed response times. Human performance varied as the range to the target increased, indicating greater dependency on the AR system as the task became more difficult. Time constraints reduced identification accuracy and usually affected unaided and aided performance similarly. Our work demonstrates the importance of simulation as a tool for understanding the effects of AR on military task performance.

Paper Details

Date Published: 14 May 2019
PDF: 14 pages
Proc. SPIE 11001, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX, 110010A (14 May 2019); doi: 10.1117/12.2518990
Show Author Affiliations
John J. Graybeal, KINEX, Inc. (United States)
Rachel T. T. Nguyen, KINEX. Inc. (United States)
Todd W. Du Bosq, U.S. Army CCDC C5ISR Ctr. NVESD (United States)

Published in SPIE Proceedings Vol. 11001:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX
Gerald C. Holst; Keith A. Krapels, Editor(s)

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