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Published in:
Mental Workload Monitoring: New Perspectives from Neuroscience Read chapter Read first chapter

2019 | OriginalPaper | Chapter

COMETA: An Air Traffic Controller’s Mental Workload Model for Calculating and Predicting Demand and Capacity Balancing

Authors : Patricia López de Frutos, Rubén Rodríguez Rodríguez, Danlin Zheng Zhang, Shutao Zheng, José Juan Cañas, Enrique Muñoz-de-Escalona

Published in: Human Mental Workload: Models and Applications

Publisher: Springer International Publishing

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Abstract

In ATM (Air Traffic Management), traffic and environment are not important by themselves. The most important factor is the cognitive work performed by the air traffic controller (ATCo). As detailed mental pictures can overcome ATCo’s limited attentional resources (causing Mental Overload), she/he can use internal strategies called abstractions to mitigate the cognitive complexity of the control task. This paper gathers the modelling, automation and preliminary calibration of the Cognitive Complexity concept. The primary purpose of this model is to support the ATM planning roles to detect imbalances and make decisions regarding the best DCB (Demand and Capacity Balancing) measures to resolve hotspots. The four parameters selected that provide meaningful operational information to mitigate cognitive complexity are Standard Flow Interactions, Flights out of Standard Flows, Potential Crossings and Flights in Evolution. The model has been integrated into a DCB prototype within the SESAR (Single European Sky ATM Research) 2020 Wave 1 during Real Time Simulations.

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previous chapter Validation of a Physiological Approach to Measure Cognitive Workload: CAPT PICARD
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Metadata
Title
COMETA: An Air Traffic Controller’s Mental Workload Model for Calculating and Predicting Demand and Capacity Balancing
Authors
Patricia López de Frutos
Rubén Rodríguez Rodríguez
Danlin Zheng Zhang
Shutao Zheng
José Juan Cañas
Enrique Muñoz-de-Escalona
Copyright Year
2019
Book
Human Mental Workload: Models and Applications

Print ISBN: 978-3-030-32422-3

Electronic ISBN: 978-3-030-32423-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-32423-0_6

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