The Role of Automation in Aviation Weather: Product Development and General Aviation Pilot Performance

Ortiz, Yolanda; Guinn, Thomas A.; King, Jayde; Thomas, R. L.; Blickensderfer, Beth

doi:10.1201/9780429458323-3

Cited by 1 publication

(2 citation statements)

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“…Prior Research. Ortiz et al (2018) developed a series of mental model measures for evaluating a pilot's understanding of preflight weather. The measures included a map of the scenario's flight area that was either blank or consisted of highlighted regions along the route of flight.…”

Section: Mental Modelsmentioning

confidence: 99%

“…A research team consisting of 2 human factors specialists, a meteorologist, and an aviation expert developed revised versions of the Ortiz et al (2018) measures. The measures aimed to capture the pilots' understanding of current and forecasted conditions regarding cloud ceiling height, visibility, and the resulting classification (VFR, MVFR, or IFR).…”

Section: Mental Model Measurementioning

confidence: 99%

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Measuring Mental Models: General Aviation Pilots’ Understanding of Preflight Weather

Kleber

Thomas

Domingo

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Weather has contributed to hundreds of General Aviation accidents. Research suggests inadequate preflight planning and lack of aviation weather knowledge are contributing factors. This study describes the development of three mental model measures (departure, enroute, and arrival) designed to assess pilots’ understanding of current and forecasted conditions. Each measure requires pilots (n=23) to evaluate weather conditions (flight category) at different regions within the flight area. A two-way mixed ANOVA examined differences in pilots’ understanding of flight category across three preflight weather briefing conditions (flight services call, self-briefing, and a combined condition) and three phases of flight (POF). No significant interaction occurred between briefing condition and POF on pilots’ ability to identify the correct flight category. However, significant differences in pilots’ understanding of weather conditions occurred between phases. Pilots were most effective at assessing flight category/weather on the enroute mental model measure and least effective at assessing weather forecasted surrounding arrival.

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Section: Mental Modelsmentioning

confidence: 99%

Section: Mental Model Measurementioning

confidence: 99%