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Predictive Alerting for Improved Aircraft State Awareness

Abstract Details

2018, Doctor of Philosophy (PhD), Ohio University, Electrical Engineering & Computer Science (Engineering and Technology).
The lack of aircraft state awareness has been one of the leading causal and contributing factors in aviation accidents. Many of these accidents were due to flight crew’s inability to understand the automation modes and properly monitor the aircraft energy and attitude state. The capability of providing flight crew with improved aircraft state awareness is essential in ensuring aviation safety. This dissertation describes predictive alerting methods that apply algorithms such as Multiple Hypothesis Prediction (MHP) on aircraft avionics outputs to predict and prevent hazardous conditions. Simulation and Human-In-The-Loop (HITL) studies results are presented to show the effectiveness of the predictive alerting method in aiding flight crew’s aircraft state awareness during some of the most confusing aircraft automate modes.
Maarten Uijt de Haag (Advisor)
Frank van Graas (Committee Member)
Michael Braasch (Committee Member)
Chris Bartone (Committee Member)
189 p.

Recommended Citations

Citations

  • Duan, P. (2018). Predictive Alerting for Improved Aircraft State Awareness [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1539871688328245

    APA Style (7th edition)

  • Duan, Pengfei. Predictive Alerting for Improved Aircraft State Awareness. 2018. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1539871688328245.

    MLA Style (8th edition)

  • Duan, Pengfei. "Predictive Alerting for Improved Aircraft State Awareness." Doctoral dissertation, Ohio University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1539871688328245

    Chicago Manual of Style (17th edition)