| Project/Area Number |
16K21002
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Cognitive science
Aerospace engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
ENTZINGER Jorg Onno 東京大学, 大学院工学系研究科(工学部), 特任研究員 (60600327)
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| Project Period (FY) |
2016-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | Flight training / Flight simulator / Human pilot / Visual information / Manual control skill / Objective evaluation / Aviation psychology / Perception training / laptop-based training / remote experiments / dimulator experiments / skill transfer / peripheral vision / field-of-view / Training support / Licensed pilots / Flight simulation / Simulator development / Data analysis / Meta-study / Pilot training / Personalized training / Pupil size / Workload evaluation / Meta-analysis / Objective feedback / Experiment / Software development / Brain Waves / Automatic analysis / Learning styles / Data synchronization / Secondary task / Training syllabus / Industry collaboration / Control style analysis / Physiological measures / 安全・ヒューマンファクターズ / 航空宇宙工学 / 誘導・航法・制御 / 認知科学 / 個別教育 |
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| Outline of Final Research Achievements |
In this project I trained 40 students basic flight manual skills in our simulator while systematically collecting their data. Another 20 participants took part in smaller side-experiments and exploratory studies. Through the analysis of this data, I was able to extract key indicators that show a student's progress. This includes not only final performance measures, bus also latent indicators of for example the trainee's level of understanding, his/her control and learning style, and stress and effort levels.
I developed tools to largely automate the analysis as well as additional modules to train specific sub-tasks in an efficient and effective manner. The visualized analysis results can be available immediately after a training flight and help the instructor to decide which exercise to start next. It can also help trainees to practice independently, and ask for a `check ride' when they feel ready.
Various parts of the analysis and training modules have gained interest from industry.
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| Academic Significance and Societal Importance of the Research Achievements |
Due to the increasing use of automation the time spent on practicing basic manual flying skills is decreasing. This research can improve flight safety by providing cost-efficient and effective training support tools. The research also shows new ways to make use of the large amount of data available.
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