Analysis of Eye-Tracking Data with Regards to the Complexity of Flight Deck Information Automation and Management - Inattentional Blindness, System State Awareness, and EFB Usage

Dill, Evan T.; Young, Steven D.

doi:10.2514/6.2015-2901

Cited by 12 publications

(16 citation statements)

References 3 publications

(5 reference statements)

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“…Previous research by our team has illustrated how demands for visual attention in the modern flight deck are significant, due largely to growing complexity [11] [23]. Eye-tracking data collected during AIME reinforces this finding.…”

Section: Applying Visual Attentionsupporting

confidence: 70%

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Flight simulation study of airplane state awareness and prediction technologies

Young

Daniels

Evans

et al. 2016

2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC)

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Airplane state awareness (ASA) is a pilot performance attribute derived from the more general attribute known as situation awareness. Airplane state alludes primarily to attitude and energy state, but also infers other state variables, such as the state of automated or autonomous systems, that can affect attitude or energy state. Recognizing that loss of ASA has been a contributing factor to recent accidents, an industry-wide team has recommended several Safety Enhancements (SEs) to resolve or mitigate the problem. Two of these SEs call for research and development of new technology that can predict energy and/or auto-flight system states, and intuitively notify or alert flight crews to future unsafe or otherwise undesired states. In addition, it is desired that future air vehicles will be able to operate with a high degree of awareness of their own well-being. This form of ASA requires onboard predictive capabilities that can inform decision-making functions of critical markers trending to unsafe states. This paper describes a high-fidelity flight simulation study designed to address the two industryrecommended SEs for current aircraft, as well as this desired self-awareness capability for future aircraft. Eleven commercial airline crews participated in the testing, completing more than 220 flights. Flight scenarios were utilized that span a broad set of conditions including several that emulated recent accidents. An extensive data set was collected that includes both qualitative data from the pilots, and quantitative data from a unique set of instrumentation devices. The latter includes a head-/eye-tracking system and a physiological measurement system. State-of-the-art flight deck systems and indicators were evaluated, as were a set of new technologies. These included an enhancement to the bank angle indicator; predictive algorithms and indications of where the auto-flight system will take the aircraft and when automation mode changes will occur or where energy-related problems may occur; and synoptic (i.e., graphical) depictions of the effects of loss of flight critical data, combined with streamlined electronic checklists. Topics covered by this paper include the research program context, test objectives, descriptions of the technologies under test, platform and operational environment setup, a summary of findings, and future work.

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Section: Applying Visual Attentionsupporting

confidence: 70%

“…Eye-tracking data collected during AIME reinforces this finding. Using the system employed for [23], an AIME-specific set of Areas of Interest (AOIs) and sub-AOIs were defined (Figure 12). Figure 13 shows how attention was distributed across the major AOIs in the previous study [11][23] versus AIME.…”

Section: Applying Visual Attentionmentioning

confidence: 99%

Flight simulation study of airplane state awareness and prediction technologies

Young

Daniels

Evans

et al. 2016

2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC)

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“…There is a necessity to understand users' perception limitations by adaptive visualizations, and this shall be integrated in the flight deck design certification process and certification requirements. The proposed augmented PFD visualization design with new, salient visual cues may reduce pilot's cognitive effort by eliminating the requirement of text-reading, and as human visual perception is affected by the saliency of an object in the field of view, it will add salient visual stimuli for critical messages on the PFD interface (Dill & Young, 2015). Pilots often must deal with time critical situations, it is important that pilots can distribute their attention effectively between the raw data and its relevant modes, as failures to manage a high-priority task in a timely manner could lead to potentially disastrous consequences (Bybee et al, 2011).…”

Section: Flight Deck Designs Swaying Pilot's Cognitive Processesmentioning

confidence: 99%

Augmented visualization cues on primary flight display facilitating pilot's monitoring performance

Horn²,

Sun

et al. 2020

International Journal of Human-Computer Studies

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There have been many aviation accidents and incidents related to mode confusion on the flight deck. The aim of this research is to evaluate human-computer interactions on a newly designed augmented visualization Primary Flight Display (PFD) compared with the traditional design of PFD. Based on statistical analysis of 20 participants interaction with the system, there are significant differences on pilots' pupil dilation, fixation duration, fixation counts and mental demand between the traditional PFD design and augmented PFD. The results demonstrated that augmented visualisation PFD, which uses a green border around the "raw data" of airspeed, altitude or heading indications to highlight activated mode changes, can significantly enhance pilots' situation awareness and decrease perceived workload. Pilots can identify the status of flight modes more easily, rapidly and accurately compared to the traditional PFD, thus shortening the response time on cognitive information processing. This could also be the reason why fixation durations on augmented PFDs were significantly shorter than traditional PFDs. The augmented visualization in the flight deck improves pilots' situation awareness as indicated by increased fixation counts related to attention distribution. Simply highlighting the parameters on the PFD with a green border in association with relevant flight mode changes will greatly reduce pilots' perceived workload and increase situation awareness. Flight deck design must focus on methods to provide pilots with enhanced situation awareness, thus decreasing cognitive processing requirements by providing intuitive understanding in time limited situations.

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“…Examples are web and print advertisements [ 23 , 24 ] and graphical representations like x-ray images of patients [ 25 ]. More complex subjects of the investigations include graphical UIs such as computer tomography interfaces [ 26 ] or spacecraft displays [ 27 , 28 ]. Further, there are single studies where eye tracking is used to evaluate highly interactive UIs of tangible products like smart TVs [ 29 ], smartwatches [ 12 , 21 ], or medical devices [ 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

“…Fixation duration (FD), describing a property of visual attention per unit, is associated with the processing depth, which when increased leads to longer fixations [ 32 - 35 ], and with the rate of information extraction [ 23 , 35 , 36 ]. DT, describing the sum of visual attention related to specific objects or features, is associated with the length of the information extraction [ 28 , 37 ]. Thus, these measurements represent attention and, in the context of handling tasks, mental workload as a subset of attention in two dimensions.…”

Section: Introductionmentioning

confidence: 99%

Value of Eye-Tracking Data for Classification of Information Processing–Intensive Handling Tasks: Quasi-Experimental Study on Cognition and User Interface Design

Wegner¹,

Lohmeyer²,

Wahlen³

et al. 2020

JMIR Hum Factors

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Background In order to give a wide range of people the opportunity to ensure and support home care, one approach is to develop medical devices that are as user-friendly as possible. This allows nonexperts to use medical devices that were originally too complicated to use. For a user-centric development of such medical devices, it is essential to understand which user interface design best supports patients, caregivers, and health care professionals. Objective Using the benefits of mobile eye tracking, this work aims to gain a deeper understanding of the challenges of user cognition. As a consequence, its goal is to identify the obstacles to the usability of the features of two different designs of a single medical device user interface. The medical device is a patient assistance device for home use in peritoneal dialysis therapy. Methods A total of 16 participants, with a subset of seniors (8/16, mean age 73.7 years) and young adults (8/16, mean age 25.0 years), were recruited and participated in this study. The handling cycle consisted of seven main tasks. Data analysis started with the analysis of task effectiveness for searching for error-related tasks. Subsequently, the in-depth gaze data analysis focused on these identified critical tasks. In order to understand the challenges of user cognition in critical tasks, gaze data were analyzed with respect to individual user interface features of the medical device system. Therefore, it focused on the two dimensions of dwell time and fixation duration of the gaze. Results In total, 97% of the handling steps for design 1 and 96% for design 2 were performed correctly, with the main challenges being task 1 insert, task 2 connect, and task 6 disconnect for both designs. In order to understand the two analyzed dimensions of the physiological measurements simultaneously, the authors propose a new graphical representation. It distinguishes four different patterns to compare the eye movements associated with the two designs. The patterns identified for the critical tasks are consistent with the results of the task performance. Conclusions This study showed that mobile eye tracking provides insights into information processing in intensive handling tasks related to individual user interface features. The evaluation of each feature of the user interface promises an optimal design by combining the best found features. In this way, manufacturers are able to develop products that can be used by untrained people without prior knowledge. This would allow home care to be provided not only by highly qualified nurses and caregivers, but also by patients themselves, partners, children, or neighbors.

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Analysis of Eye-Tracking Data with Regards to the Complexity of Flight Deck Information Automation and Management - Inattentional Blindness, System State Awareness, and EFB Usage

Cited by 12 publications

References 3 publications

Flight simulation study of airplane state awareness and prediction technologies

Flight simulation study of airplane state awareness and prediction technologies

Augmented visualization cues on primary flight display facilitating pilot's monitoring performance

Value of Eye-Tracking Data for Classification of Information Processing–Intensive Handling Tasks: Quasi-Experimental Study on Cognition and User Interface Design

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