Maneuver Identification Challenge

• URL: http://arxiv.org/abs/2108.11503v1
• Date: Wed, 25 Aug 2021 22:41:45 GMT
• Title: Maneuver Identification Challenge
• Authors: Kaira Samuel, Vijay Gadepally, David Jacobs, Michael Jones, Kyle McAlpin, Kyle Palko, Ben Paulk, Sid Samsi, Ho Chit Siu, Charles Yee, Jeremy Kepner
• Abstract summary: The Maneuver Identification Challenge provides thousands of trajectories collected from pilots practicing in flight simulators. The first challenge is separating physically plausible (good) trajectories from unfeasible (bad) trajectories. The second challenge is to label trajectories with their intended maneuvers and to assess the quality of those maneuvers.
• Score: 6.154050700252063
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: AI algorithms that identify maneuvers from trajectory data could play an important role in improving flight safety and pilot training. AI challenges allow diverse teams to work together to solve hard problems and are an effective tool for developing AI solutions. AI challenges are also a key driver of AI computational requirements. The Maneuver Identification Challenge hosted at maneuver-id.mit.edu provides thousands of trajectories collected from pilots practicing in flight simulators, descriptions of maneuvers, and examples of these maneuvers performed by experienced pilots. Each trajectory consists of positions, velocities, and aircraft orientations normalized to a common coordinate system. Construction of the data set required significant data architecture to transform flight simulator logs into AI ready data, which included using a supercomputer for deduplication and data conditioning. There are three proposed challenges. The first challenge is separating physically plausible (good) trajectories from unfeasible (bad) trajectories. Human labeled good and bad trajectories are provided to aid in this task. Subsequent challenges are to label trajectories with their intended maneuvers and to assess the quality of those maneuvers.

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