Augmenting Flight Training with AI to Efficiently Train Pilots

• URL: http://arxiv.org/abs/2210.06683v1
• Date: Thu, 13 Oct 2022 02:35:24 GMT
• Title: Augmenting Flight Training with AI to Efficiently Train Pilots
• Authors: Michael Guevarra (1), Srijita Das (2 and 3), Christabel Wayllace (2 and 3), Carrie Demmans Epp (2), Matthew E. Taylor (2 and 3), Alan Tay (1) ((1) Delphi Technology Corp, (2) University of Alberta, (3) Alberta Machine Intelligence Institute)
• Abstract summary: We propose an AI-based pilot trainer to help students learn how to fly aircraft. An AI agent uses behavioral cloning to learn flying maneuvers from qualified flight instructors. The system uses the agent's decisions to detect errors made by students and provide feedback to help students correct their errors.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose an AI-based pilot trainer to help students learn how to fly aircraft. First, an AI agent uses behavioral cloning to learn flying maneuvers from qualified flight instructors. Later, the system uses the agent's decisions to detect errors made by students and provide feedback to help students correct their errors. This paper presents an instantiation of the pilot trainer. We focus on teaching straight and level flying maneuvers by automatically providing formative feedback to the human student.

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