Cognitive Workload and Learning Assessment During the Implementation of a Next-Generation Air Traffic Control Technology Using Functional Near-Infrared Spectroscopy

TLDR

Neuroimaging technologies such as functional near‑infrared spectroscopy can provide brain‑based performance metrics to assess safety and performance of operators in high‑risk fields. This paper objectively and subjectively examines the cognitive workload of air traffic control specialists using a next‑generation conflict resolution advisory. The study analyzed a learning effect across a three‑day, nine‑session training period. Increasing aircraft counts produced credible workload differences and a possible fNIR saturation, while a learning effect was evident between Day 1 and Day 2 but not Day 3, demonstrating that objective fNIR measures offer advantages over subjective keypad assessments.

Abstract

Neuroimaging technologies, such as functional near-infrared spectroscopy (fNIR), could provide performance metrics directly from brain-based measures to assess safety and performance of operators in high-risk fields. In this paper, we objectively and subjectively examine the cognitive workload of air traffic control specialists utilizing a next-generation conflict resolution advisory. Credible differences were observed between continuously increasing workload levels that were induced by increasing the number of aircraft under control. In higher aircraft counts, a possible saturation in brain activity was realized in the fNIR data. A learning effect was also analyzed across a three-day/nine-session training period. The difference between Day 1 and Day 2 was credible, while there was a noncredible difference between Day 2 and Day 3. The results presented in this paper indicate some advantages in objective measures of cognitive workload assessment with fNIR cortical imaging over the subjective workload assessment keypad.