Enhanced/Synthetic Vision Systems: Human Factors Research and Implications for Future Systems

Foyle, David C.; Ahumada, Albert J.; Larimer, James; Sweet, Barbara T.

doi:10.4271/921968

Cited by 22 publications

(16 citation statements)

References 19 publications

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“…10 Investigators have found that the display clutter and field-of-view issues already mentioned for tunnel-only displays are even more of an issue when combined with synthetic vision, and additional human factors issues such as pilot over-fixation on the symbology are introduced. 11 There have been many more studies in this area of tunnel and synthetic vision situational awareness augmentation, but this brief survey illustrates some of the issues that were also of concern during our work here at Boeing.…”

Section: B Synthetic Vision-based Studiesmentioning

confidence: 96%

Flight Simulation Architecture for Tunnel-in-the-Sky Guidance and Synthetic Vision

Brychcy

Shanmugasundaram

Allen

et al. 2004

Journal of Aerospace Computing, Information, and Communication

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This paper will focus on the practical incorporation of "tunnel-in-the-sky" and synthetic vision concepts from a flight simulation software perspective. Piloted, rotorcraft flight simulation analysis of these concepts has been an ongoing activity in the Boeing Flight Simulation Laboratory in Philadelphia. The theoretical basis and advantages in augmenting pilot situational awareness was well presented by Robert R. Wilkins. 1 In this paper, the technical issues involving design architecture, visual perception and verification of these concepts will be addressed. Some of these issues include architecture optimization for future enhancements, tunnel correlation and conformality with out-the-window terrain, validation of pilot visual cues and integration of tunnel and synthetic vision concepts. Future work and directions will also be discussed, for both tunnel symbology-based guidance and synthetic vision situational awareness, in the context of practical realization in a rotorcraft flight simulation environment.acceleration of gravity T H = tunnel height -ft H B = barometric altitude -ft T HDG = tunnel heading -deg H P = pressure altitude -ft T T = tunnel turn radius -deg F F = function factor -normalized T W = tunnel width -ft F pv Δθ = flight path vector delta pitch -deg T Y = tunnel yaw -deg F pv Δψ = flight path vector delta yaw -deg V A = true airspeed -kn K PHI = gain on bank angle V C = calibrated airspeed -kn K TAE = gain on track angle V G = groundspeed -kn K XTD = gain on cross track deviation V R = reference speed -kn N G = north cig coordinate -ft V RC = vertical velocity -ft/s N Xwp = next waypoint index -unitless X L = aircraft longitude -€ ˙ P O = push-over rate -deg (deg/min/s) S L = tunnel segment length -feet XTD = aircraft cross track S S = tunnel segment spacing -feet deviation -perpindicular TAE = aircraft track angle error -difference distance from aircraft between tunnel course and aircraft center of gravity to tunnel ground track angle -deg ground track -ft T A = tunnel altitude -ft Y L = aircraft latitude -(deg/min/s) € ˙ φ = aircraft roll rate -deg/s Z B = tunnel flight profile height -ft θ = pitch angle -deg BRYCHCY ET AL. 240 ΔP Y = power cue vertical offset -in. (display) ϑ (5) = fifth order polynomial ΔT = simulation execution time -s quantity -unitless ΔT C = command-frame time -s ψ = aircraft heading -deg ΔT F = lead-frame time -s € ˙ ψ = aircraft yaw rate deg/s ΔT L = look-ahead time -s ψ M = aircraft magnetic heading -Δθ Y = pitch cue vertical offset -in. (display) deg φ = aircraft bank angle -deg ψ T = aircraft true heading -deg

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Section: B Synthetic Vision-based Studiesmentioning

confidence: 96%

Flight Simulation Architecture for Tunnel-in-the-Sky Guidance and Synthetic Vision

Brychcy

Shanmugasundaram

Allen

et al. 2004

Journal of Aerospace Computing, Information, and Communication

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“…Distortion: The polynomials (15) and (16) model the windshield distortion. To display the image generated in the previous step correctly, we apply an inverse distortion on the image.…”

Section: Two-pass Renderingmentioning

confidence: 99%

“…The idea of using HUDs as an Augmented Reality device was originally introduced and explored for avionic applications [15,10,9,21]. Here, pilots are assisted in navigating the plane safely in the air or on the ground by visualizing flight corridors or by highlighting taxiways when the visibility is low.…”

Section: Introductionmentioning

confidence: 99%

A camera-based calibration for automotive augmented reality Head-Up-Displays

Wientapper

Wuest

Rojtberg

et al. 2013

2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

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Using Head-up-Displays (HUD) for Augmented Reality requires to have an accurate internal model of the image generation process, so that 3D content can be visualized perspectively correct from the viewpoint of the user. We present a generic and cost-effective camera-based calibration for an automotive HUD which uses the windshield as a combiner. Our proposed calibration model encompasses the view-independent spatial geometry, i.e. the exact location, orientation and scaling of the virtual plane, and a view-dependent image warping transformation for correcting the distortions caused by the optics and the irregularly curved windshield. View-dependency is achieved by extending the classical polynomial distortion model for cameras and projectors to a generic five-variate mapping with the head position of the viewer as additional input. The calibration involves the capturing of an image sequence from varying viewpoints, while displaying a known target pattern on the HUD. The accurate registration of the camera path is retrieved with state-of-the-art vision-based tracking. As all necessary data is acquired directly from the images, no external tracking equipment needs to be installed. After calibration, the HUD can be used together with a head-tracker to form a head-coupled display which ensures a perspectively correct rendering of any 3D object in vehicle coordinates from a large range of possible viewpoints. We evaluate the accuracy of our model quantitatively and qualitatively

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“…Background of synthetic vision and human factor issues has been briefed in a panel discussion 6 from the perspective of government, academic, military and industry. D.C. Foyle 7 , et al have reviewed some of the research related to enhance synthetic vision systems. Out-of-the-window viewing in low visibility weather with limited display characteristics, that may result in degradation of the visual cues, is discuss.…”

Section: Synthetic Visionmentioning

confidence: 99%

Real-time Interactive Steerable Scientific Visualisation of Free Surface Flow in the Context of Synthetic Vision

Lingaraju¹,

Nithiarasu²,

Kusuma³

et al. 2011

DSJ

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The existing techniques in the context of fluid modelling and simulation have been reviewed. Generic framework that enables an easy integration of various modules has been developed, extending the work to real-time simulation and visualisation, and developed user interaction during run-time using the concept of computational steering. In the generic framework developed, a new class of visualisation technique that simplifies the visualisation tasks of a scientist has been identified. Investigating these techniques is important as the tools such as visualisation tool kit (VTK) and VTK designer are freely available (Open Source) and easy to integrate. A technique for interactive visualisation of the free surface flow, that introduces the concepts of geometrical steering and properties steering, has been developed. These techniques constitute computational steering. The concept of real-time interactive scientific visualisation using a surface flow application has been demonstrated. As a proof of concept, the behaviour of flow is simulated and visualised during training in a virtual environment on a desktop computer. It is expected that the generic framework, device, interface, and simulation engine, used in this work will not only have a significant impact in the area of free surface flow, but also in real-time applications such as synthetic vision in avionics. The underlying formulation/methodology involved in parametric approach is explained.

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Enhanced/Synthetic Vision Systems: Human Factors Research and Implications for Future Systems

Cited by 22 publications

References 19 publications

Flight Simulation Architecture for Tunnel-in-the-Sky Guidance and Synthetic Vision

Flight Simulation Architecture for Tunnel-in-the-Sky Guidance and Synthetic Vision

A camera-based calibration for automotive augmented reality Head-Up-Displays

Real-time Interactive Steerable Scientific Visualisation of Free Surface Flow in the Context of Synthetic Vision

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