The impact of flight simulation in aerospace

Allerton, D. J.

doi:10.1017/s0001924000004231

Cited by 59 publications

(36 citation statements)

References 17 publications

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“…One of these methods is based on assessment of changes in dynamic behaviour during time, in other words, in different phases of the training. This method is using identified parameters of the pilot behaviour model, see (2). Individual parameters of this model, especially T2, T3, and τ, represent the current pilot status, from his dynamic properties point of view, corresponding to his approach and style of flying.…”

Section: Methods Based On Modelling Human Behaviourmentioning

confidence: 99%

“…Their flying inexperience is clearly visible here. From all the tests with this pilot group, using identification algorithms according to equations (2) and 3, transfer function parameters were determined for pilot behaviour without any previous flying experience.…”

Section: Pilots Without Previous Experiencementioning

confidence: 99%

“…Mean-root-square error, determining the accuracy of the interpolated output curve from the control stick movement, is just above 0.1. Such an error is considered good when using flight simulators and the transfer function is calculated from equation (2). Individual parameters of the transfer function for pilot behaviour have different values for each test.…”

Section: Pilots With Practical Experience On Z-142cafmentioning

confidence: 99%

“…The use of simulators provides a uniformed system of preparation of aviation staff and it enables the acquisition of ingrained and stable flying habits as well as the refreshing of existing knowledge. It also uniforms routine procedures enabling various solutions to random or standard situations [2].…”

Section: Introductionmentioning

confidence: 99%

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Using Aviation Simulation Technologies for Pilot Modelling and Flight Training Assessment

Bořil

Jirgl

Jalovecky

2017

AiMT

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This paper summarises many years of the results of the development and modelling of human behaviour while flying an aircraft, from a flight automation point of view. The introduction presents the challenges of describing and modelling human behaviour. Based on that knowledge, options for acquiring parameters for a pilot behaviour model are described. Then, analysis of pilot response is presented, acquired from many tests on two simulators (stationary and motion-platform). These experimental tests are pilot responses to a visual stimulus and also partially to motion stimulus-step change in flight altitude where the task of the pilot is to return the flight, as quickly as possible to the original flight altitude. Due to the vast amount of test data files-missions from each test-the authors rewrote the identification algorithms for batch data processing and utilised a Salamon supercomputer located at Technical University of Ostrava. In the first phase of implementation of the identification algorithms, the calculations were 4 times faster, and after rewriting the algorithms for parallel calculations, the authors expect the speed to increase more than 10 times.

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Section: Methods Based On Modelling Human Behaviourmentioning

confidence: 99%

Section: Pilots Without Previous Experiencementioning

confidence: 99%

Section: Pilots With Practical Experience On Z-142cafmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using Aviation Simulation Technologies for Pilot Modelling and Flight Training Assessment

Bořil

Jirgl

Jalovecky

2017

AiMT

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“…In many other professional fields "simulator time" is logged and contributes towards the final assessment goals for gaining/retaining a licence (e.g. a pilot's licence; (Allerton, 2010)) and there is huge scope to expand this practice into the domain of driving. One counter-argument against increased use of simulation for training/assessment is that perhaps in the future cars will no longer need drivers.…”

Section: The Future Of Driving Assessmentmentioning

confidence: 99%

Looking to the future of visual assessment using driving simulation

Wilkie

Mole

2017

Scand J Optom Vis Sci

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Visual function is considered uniquely important for driving because it provides multiple critical sources of information that when combined ensures successful steering. There are, however, additional cognitive functions that are essential for the driver to be able to dynamically respond to the world and make predictions about the scene, as well as the behaviour of other road users. Given the complexity of driving through a busy urban environment it should be no surprise that simple tests of visual acuity seem to have weak explanatory power in terms of increased crash risk when driving. Despite this, fitness to drive still includes a formal assessment of visual acuity, with poor scores being used to revoke the driving licence. The "gold standard" measure of driving ability remains the on-road driving test but compared to visual tests they are fairly uncontrolled, susceptible to great variation depending on the road conditions, and are unable to reliably detect subtle visual deficits. To address some of the limitations of these existing tests we use examples from two simulator settings (steering control and hazard detection) that highlight the merits of using driving simulation in order to control the visual conditions and probe specific functional capabilities of drivers. When used in conjunction with visual tests these methods will not only determine whether the core functions of driving are intact but also be able to provide richer feedback to individuals about the nature of their deficits. There are many exciting possibilities using simulation techniques to establish predictive relationships between routine visual testing and driving performance, ultimately aiming for better, more reliable assessment of fitness to drive. SammendragSynsfunksjonen betraktes som enestående viktig for bilkjøring fordi den bidrar til flere kritiske informasjonskilder som sammen sikrer trygg kontroll av bilen. Men det finnes i tillegg andre kognitive funksjoner som er nødvendige for at en bilfører skal kunne reagere dynamisk og kunne forutse både hendelser i trafikkbildet og andre trafikanters handlinger. Tatt i betraktning kompleksiteten av å kjøre i trafikkerte, tettbygde strøk, er det ikke overraskende at en enkel test av synsstyrke sjelden kan forklare fullstendig risikoen for kollisjoner ved bilkjøring. Til tross for dette brukes fortsatt synsstyrke som et mål i den formelle undersøkelsen når man skal avgjøre om en person er egnet til å føre motorvogn, og dårlige resultater på synstesten fører til inndragelse av førerkortet. Kjøreevne måles fortsatt med praktisk prøve, men sammenlignet med tester av synsfunksjonen er disse prøvene vanskelige å kontrollere, sterkt varierende avhengig av veiforholdene, og ikke i stand til å avsløre små synsdefekter. For å studere noen av begrensningene ved disse eksisterende prøvene bruker vi eksempler fra to simulatorsettinger (styrekontroll og evne til å oppdage fare) som viser fordelene med å bruke kjøresimulator for å kontrollere synsforholdene og teste bestemte funkjonelle ferdighet...

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Evaluating Simulation as a Teaching Tool in Neurosurgery

Rothstein

Selman

2015

Virtual Mentor

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The impact of flight simulation in aerospace

Cited by 59 publications

References 17 publications

Using Aviation Simulation Technologies for Pilot Modelling and Flight Training Assessment

Using Aviation Simulation Technologies for Pilot Modelling and Flight Training Assessment

Looking to the future of visual assessment using driving simulation

Evaluating Simulation as a Teaching Tool in Neurosurgery

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