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A fuzzy-hybrid SHELL framework for predicting air traffic conflict detection and resolution performance: a human-factors perspective

Published online by Cambridge University Press:  27 March 2025

Fitri Trapsilawati Open the ORCID record for Fitri Trapsilawati [Opens in a new window]
Fitri Trapsilawati*
Affiliation:
Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jalan Grafika no. 2, Yogyakarta 55281, Indonesia
*
Email: [email protected]
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Abstract

The complex tasks of air traffic control (ATC) and the various factors affecting its operation have shed light on the need to build a model to predict conflict detection and resolution (CDR) performance within a traffic situation. This study aimed at developing a fuzzy-hybrid framework for quantifying various aspects in ATC consisting of the software, hardware, environment, liveware and organisation (i.e. the SHELL model) to predict CDR performance. The proposed fuzzy-hybrid SHELL framework in this study was tested using metadata from 10 prior studies in ATC. The results showed a highly accurate prediction, as indicated by the RMSE and MAPE values of 0⋅09 and 5⋅36%, respectively, indicating a high consistency of 90⋅92% for predicting the CDR performance. This framework offers a promising approach for Air Navigation Service Providers (ANSPs) to maintain air traffic safety and improve ATC operations efficiency.

Keywords

fuzzy logicSHELLconflict detection and resolution
Type
Research Article
Information
The Journal of Navigation , First View , pp. 1 - 18
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Copyright
Copyright © The Author(s), 2025. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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