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Thesis-Sai K. Nittala.pdf (879.86 KB)

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Prediction of Pilot Skill Level and Workload for Sliding-Scale Autonomous Systems

Nittala, Sai Kameshwar Rao
http://orcid.org/0000-0002-8989-7920
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513180622059467

Abstract Details

2017, Master of Science, University of Toledo, Electrical Engineering.
There has been tremendous growth in the quality of communication in the human-computer interaction field. Some of the focus areas have included intelligent adaptive interfaces, and multi modality. An emerging topic in this field of research involves optimal collaboration between humans and machines to achieve a particular goal. One approach to such a goal involves sliding-scale autonomy, in which a machine is designed to dynamically adjust between different levels of autonomy based on a variety of factors, such as the skill level, workload, and behavior of the human operator. This thesis proposes a system to dynamically predict skill level and workload for pilots on a flight simulator using classification and regression algorithms, respectively. The proposed system uses the pilot's heart rate variability and flight control data. The flight control data includes pilot interactions, such as throttle and aileron, and flight sensor data, such as latitude and longitude. A user study on fifteen pilots was conducted, each flying the same five predefined routes on a flight simulator. The results indicate that the flight control data alone is sufficient to provide a near perfect classification of a pilot's skill level of either expert or novice. On the other hand, it was found that a combination of flight control and heart rate data produced a more accurate estimate of mental workload and effort. The findings provide the first step towards a sliding-scale autonomous system for airplane pilots.
Kevin Xu (Committee Chair)
Vijay Devabhaktuni (Committee Co-Chair)
Ahmad Javaid (Committee Member)
Scott Pappada (Committee Member)
91 p.
Computer Science; Electrical Engineering; Engineering
human-machine teaming, mental workload, flight simulator, heart rate variability

Recommended Citations

Citations

  • Nittala, S. K. R. (2017). Prediction of Pilot Skill Level and Workload for Sliding-Scale Autonomous Systems [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513180622059467

    APA Style (7th edition)

  • Nittala, Sai Kameshwar Rao. Prediction of Pilot Skill Level and Workload for Sliding-Scale Autonomous Systems. 2017. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513180622059467.

    MLA Style (8th edition)

  • Nittala, Sai Kameshwar Rao. "Prediction of Pilot Skill Level and Workload for Sliding-Scale Autonomous Systems." Master's thesis, University of Toledo, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513180622059467

    Chicago Manual of Style (17th edition)

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© 2017, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.