Flying a fighter jet can be challenging, so one training squadron is exploring how artificial intelligence could help craft better aviators.
have crashed planes this year. Post-crash investigations, pulling from the recorded avionics and telemetry data of the planes, can reveal the specific causes of error, from mechanical failure to choices made by pilots.
Planes capture this data, the avionics and flight telemetry, many times a second, creating a record of time, speed, and position. It’s a massive data set produced by every flight, and one that is hard for humans to process without the aid of data analysis tools. At present, that data can be used in debriefings, where pilots sit after a mission and watch the flights play out on a monitor in the space of a couple hours.
“What air speed you execute an approach and a landing in a Strike Eagle [an F-15E] is dependent on your fuel weight,” says Poppler. “And so [the prototype tool] can actually calculate final approach speed based on your fuel weight.
.” The tool can analyze flights in a simulator the same way it can analyze flight recorder data, and bring greater understanding of normal operations and deviations to flight analysis. With optimization, it can also break from a one-size-fits-all approach to teaching pilots. Every year, the training squadron takes in 40 to 50 pilots, with the expectation of graduating as many as possible to then serve 10-year commitments in the Air Force.
This can also apply to getting pilots ready for missions. If a specific mission calls for the F-15Es to be used as ground bombers, a commander could look at the record from her squadron and pick pilots based on how well they have flown those missions in the past.
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