Computational modeling to predict pilot's expectation of the aircraft state given vestibular and visual cues

Can Onur, Anil Bozan, Amy Pritchett

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Loss of Control (LOC) accidents are a major threat for aviation, and contribute the highest risk for fatalities in all aviation accidents. The major contributor to LOC accidents is pilot spatial disorientation (SD), which accounts for roughly 32% of all LOC accidents. A pilot experiences SD during flight when he/she fails to sense correctly the motion, and/or attitude of the aircraft. In essence, the pilot's expectation of the aircraft's state deviates from reality. This deviation results from a number of underlying mechanisms of SD, such as distraction, failure to monitor flight instruments, and vestibular illusions. Previous researchers have developed computational models to understand those mechanisms. However, the models are limited in scope, as they do not model pilot expertise and have a small span of flight regimes to test with. This research proposes a new pilot model to predict the best-possible-pilot-expectation of the aircraft state given vestibular and visual cues. The proposed pilot model is in the form of a model-based observer (MBO), which provides the infrastructure needed to establish an expert pilot model. Experts are known to form an internal model of the operated system due to training/experience, which allows the expert to generate internal expectations of the system states. Pilot's internal expectations are enhanced by the presence of information fed through the pilot's sensory systems. The proposed pilot model integrates a continuous vestibular sensory model and a discrete visual-sampling sensory model to take account for the influence of the pilot's sensory system on his/her expectation of the aircraft state. The computational model serves to investigate the underlying mechanisms of SD during flight and provide a quantitative analysis tool to support flight deck and countermeasure designs.

Original languageEnglish (US)
Title of host publication2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014
PublisherIEEE Computer Society
Pages271-276
Number of pages6
ISBN (Print)9781479948369
DOIs
StatePublished - Jan 1 2014
Event2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014 - Charlottesville, VA, United States
Duration: Apr 25 2014Apr 25 2014

Publication series

Name2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014

Other

Other2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014
CountryUnited States
CityCharlottesville, VA
Period4/25/144/25/14

Fingerprint

Aircraft
Accidents
Aircraft accidents
Aviation
Sampling
Chemical analysis

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Control and Systems Engineering

Cite this

Onur, C., Bozan, A., & Pritchett, A. (2014). Computational modeling to predict pilot's expectation of the aircraft state given vestibular and visual cues. In 2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014 (pp. 271-276). [6829914] (2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014). IEEE Computer Society. https://doi.org/10.1109/SIEDS.2014.6829914
Onur, Can ; Bozan, Anil ; Pritchett, Amy. / Computational modeling to predict pilot's expectation of the aircraft state given vestibular and visual cues. 2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014. IEEE Computer Society, 2014. pp. 271-276 (2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014).
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abstract = "Loss of Control (LOC) accidents are a major threat for aviation, and contribute the highest risk for fatalities in all aviation accidents. The major contributor to LOC accidents is pilot spatial disorientation (SD), which accounts for roughly 32{\%} of all LOC accidents. A pilot experiences SD during flight when he/she fails to sense correctly the motion, and/or attitude of the aircraft. In essence, the pilot's expectation of the aircraft's state deviates from reality. This deviation results from a number of underlying mechanisms of SD, such as distraction, failure to monitor flight instruments, and vestibular illusions. Previous researchers have developed computational models to understand those mechanisms. However, the models are limited in scope, as they do not model pilot expertise and have a small span of flight regimes to test with. This research proposes a new pilot model to predict the best-possible-pilot-expectation of the aircraft state given vestibular and visual cues. The proposed pilot model is in the form of a model-based observer (MBO), which provides the infrastructure needed to establish an expert pilot model. Experts are known to form an internal model of the operated system due to training/experience, which allows the expert to generate internal expectations of the system states. Pilot's internal expectations are enhanced by the presence of information fed through the pilot's sensory systems. The proposed pilot model integrates a continuous vestibular sensory model and a discrete visual-sampling sensory model to take account for the influence of the pilot's sensory system on his/her expectation of the aircraft state. The computational model serves to investigate the underlying mechanisms of SD during flight and provide a quantitative analysis tool to support flight deck and countermeasure designs.",
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Onur, C, Bozan, A & Pritchett, A 2014, Computational modeling to predict pilot's expectation of the aircraft state given vestibular and visual cues. in 2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014., 6829914, 2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014, IEEE Computer Society, pp. 271-276, 2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014, Charlottesville, VA, United States, 4/25/14. https://doi.org/10.1109/SIEDS.2014.6829914

Computational modeling to predict pilot's expectation of the aircraft state given vestibular and visual cues. / Onur, Can; Bozan, Anil; Pritchett, Amy.

2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014. IEEE Computer Society, 2014. p. 271-276 6829914 (2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Loss of Control (LOC) accidents are a major threat for aviation, and contribute the highest risk for fatalities in all aviation accidents. The major contributor to LOC accidents is pilot spatial disorientation (SD), which accounts for roughly 32% of all LOC accidents. A pilot experiences SD during flight when he/she fails to sense correctly the motion, and/or attitude of the aircraft. In essence, the pilot's expectation of the aircraft's state deviates from reality. This deviation results from a number of underlying mechanisms of SD, such as distraction, failure to monitor flight instruments, and vestibular illusions. Previous researchers have developed computational models to understand those mechanisms. However, the models are limited in scope, as they do not model pilot expertise and have a small span of flight regimes to test with. This research proposes a new pilot model to predict the best-possible-pilot-expectation of the aircraft state given vestibular and visual cues. The proposed pilot model is in the form of a model-based observer (MBO), which provides the infrastructure needed to establish an expert pilot model. Experts are known to form an internal model of the operated system due to training/experience, which allows the expert to generate internal expectations of the system states. Pilot's internal expectations are enhanced by the presence of information fed through the pilot's sensory systems. The proposed pilot model integrates a continuous vestibular sensory model and a discrete visual-sampling sensory model to take account for the influence of the pilot's sensory system on his/her expectation of the aircraft state. The computational model serves to investigate the underlying mechanisms of SD during flight and provide a quantitative analysis tool to support flight deck and countermeasure designs.

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Onur C, Bozan A, Pritchett A. Computational modeling to predict pilot's expectation of the aircraft state given vestibular and visual cues. In 2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014. IEEE Computer Society. 2014. p. 271-276. 6829914. (2014 IEEE Systems and Information Engineering Design Symposium, SIEDS 2014). https://doi.org/10.1109/SIEDS.2014.6829914