Assessment of pilots' training efficacy as a safety barrier in the context of Enhanced Flight Vision Systems (EFVS)
Authors: Dimitrios Ziakkas, Konstantinos Pechlivanis, Brian Dillman
Abstract: Aviation and air travel have always been among the businesses at the forefront of technological advancement throughout history. Both the International Air Transportation Authority's (IATA) Technology Roadmap (IATA, 2019) and the European Aviation Safety Agency's (EASA) Artificial Intelligence (AI) roadmap (EASA, 2020) propose an outline and assessment of ongoing technological prospects that change the aviation environment with the implementation of AI from the initial phases. New technology increased the operational capabilities of airplanes in adverse weather. An enhanced flight vision system (EFVS) is a piece of aircraft equipment that captures and displays a scene image for the pilot, allowing for improved scene and object detection. Moreover, an EFVS is a device that enhances the pilot's vision to the point where it is superior to natural sight. An EFVS has a display for the pilot, which can be a head-mounted display or a head-up display, and image sensors such as a color camera, infrared camera, or radar. A combined vision system can be made by combining an EFVS with a synthetic vision system. A forward-looking infrared camera, also known as an enhanced vision system (EVS), and a Head-Up Display (HUD) are used to form the EFVS. Two aircraft types can house an EFVS: fixed-wing (airplane) and rotary-wing (helicopter).Several operators argue that the use of Enhanced Flight Vision Systems (EFVS) may be operated without the prior approval of the competent authority, assuming that the flight procedures, equipment, and pilot safety barriers are sufficiently robust. This research aims to test pilots' readiness levels with no or little exposure to EFVS to use such equipment (EASA, 2020). Moreover, the Purdue simulation center aims to validate this hypothesis. The Purdue human systems integration team is developing a test plan that could be easily incorporated into the systems engineering test plan to implement Artificial Intelligence (AI) in aviation training globally and evaluate the results. Based on guidelines from the International Air Transport Association (IATA), the Purdue University School of Aviation and Transportation Technology (SATT) professional flying program recognizes technical and nontechnical competencies. Furthermore, the Purdue Virtual Reality research roadmap is focused on the certification process (FAA, EASA), implementation of an AI training syllabus following a change management approach, and introduction of AI standardization principles in the global AI aviation ecosystem.
Keywords: Artificial intelligence (AI), Enhanced Flight Vision Systems (EFVS), Training efficacy, AI learning assurance.
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