Air Traffic Controller Cognitive Workload Level Prediction using Conformal Dynamical Graph Learning

Published in Advanced Engineering Informatics, 2023 · arXiv

Representative figure for this publication
Human-in-the-loop experiment at the ASU TRACON simulation facility: retired controllers manage KPHX arrival scenarios with pseudo-pilots while workload and situational awareness probes collect ratings every three minutes.

Predicts controller cognitive workload in real time on dynamical airspace graphs, with conformal-prediction guarantees on the estimates.

Representative publication of this research line.

Recommended citation

@article{pang2023air,
  title = {Air Traffic Controller Cognitive Workload Level Prediction using Conformal Dynamical Graph Learning},
  author = {Pang, Y. and Hu, J. and Lieber, C. and Cooke, N. and Liu, Y.},
  journal = {Advanced Engineering Informatics},
  volume = {57},
  pages = {102113},
  year = {2023},
  eprint = {2307.10559},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  url = {https://arxiv.org/abs/2307.10559}
}