Situational Awareness based Performance Evaluation of APR 1400 Engineered Safety Features - Component Control Actuation Systems using Augmented Reality

2016 ◽  
Vol 26 (s1) ◽  
pp. 372-385
Author(s):  
Mwongeera Murungi ◽  
J. C. Jung
Author(s):  
I. Murph ◽  
M. McDonald ◽  
K. Richardson ◽  
M. Wilkinson ◽  
S. Robertson ◽  
...  

Within distracting environments, it is difficult to maintain attentional focus on complex tasks. Cognitive aids can support attention by adding relevant information to the environment, such as via augmented reality (AR). However, there may be a benefit in removing elements from the environment, such as irrelevant alarms, displays, and conversations. De-emphasis of distracting elements is a type of AR called Diminished Reality (DR). Although de-emphasizing distraction may help focus on a primary task, it may also reduce situational awareness (SA) of other activities that may become relevant. In the current study, participants will assemble a medical ventilator during a simulated emergency while experiencing varying levels of DR. Participants will also be probed to assess secondary SA. We anticipate that participants will have better accuracy and completion times in the full DR conditions but their SA will suffer. Future applications include the design of future DR systems and improved training methods.


Author(s):  
Chris Wickens ◽  
Gaia Dempsey ◽  
Andrew Pringle ◽  
Lucas Kazansky ◽  
Stefanie Hutka

We developed a 3D augmented reality head mounted display (DARSADS-SVS HMD) interface to support the Joint Tactical Air Controller (JTAC). The JTAC’s job is to integrate information about enemy attack units and nearby friendly forces and direct aircraft equipped with weapons to neutralize the enemy via close air support (CAS), while also safely routing air traffic. The JTAC’s numerous and often overlapping tasks involve maintaining detailed situational awareness (SA) of a large quantity of information, and making rapid decisions that carry life-or-death consequences. Thus, the JTAC role requires many different cognitive operations across different mission phases. Designing an effective human-factored system that supports maximum SA while minimizing cognitive load required us to harness computational cognitive models of SA-supporting visual scanning, display layout, 3D frame-of-reference transformations, clutter, legibility and working memory. We applied such models to different phases of the JTAC mission (e.g., airspace management, call-for-fire), establishing a Figure of Merit (FOM) for each given design by summing FOMs across models, thus creating a mechanism to evaluate designs based upon their balanced impact on competing cognitive drivers. Models were differentially weighted for each phase, according to the relative importance of the relevant cognitive process to the phase in question. In this research paper, we illustrate two such design comparisons.


2017 ◽  
Vol 12 ◽  
pp. 13 ◽  
Author(s):  
Dragoș Datcu ◽  
Leon Rothkrantz

Car simulators are essential for training and for analyzing the behavior, the responses and the performance of the driver. Augmented Reality (AR) is the technology that enables virtual images to be overlaid on views of the real world. Affective Computing (AC) is the technology that helps reading emotions by means of computer systems, by analyzing body gestures, facial expressions, speech and physiological signals. The key aspect of the research relies on investigating novel interfaces that help building situational awareness and emotional awareness, to enable affect-driven remote collaboration in AR for car driving simulators. The problem addressed relates to the question about how to build situational awareness (using AR technology) and emotional awareness (by AC technology), and how to integrate these two distinct technologies [4], into a unique affective framework for training, in a car driving simulator.


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