arXiv Machine Learning June 26, 2026 By Hong-ah Chai, Seokbin Yoon, Keumjin Lee

Learning to Explain Air Traffic Situation

Read the original on arXiv Machine Learning →

arXiv:2502. 10764v4 Announce Type: replace Abstract: Understanding how air traffic controllers construct a mental 'picture' of complex air traffic situations is crucial but remains a challenge due to the inherently intricate, high-dimensional interactions between aircraft, pilots, and controllers.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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