A prediction model of the mental workload of pilots based on improved multiple resource theory

Purpose With the development of modern military technology, new combat equipment increased function-ality, and at the same time increased the workload of the operator. The goal of this study is to accurately and objectively predict the mental workload of the pilots of receiver aircraft (RA) during aerial refueling. Design/methodology/approach The prediction model is based on the multiple resource theory (MRT). Level-based weight as-sessment (LBWA) and the decision-making trial and evaluation laboratory–interpretative structural modeling (DEMATEL-ISM) method are used to determine the weights of mental resource channels in terms of importance and relevance, respectively, due to arithmetic accuracy and ability to analyze at multiple levels of hierarchy. Furthermore, the Mental Workload Dynamic Model (MWDM) was introduced to propose a Mental Workload Prediction Model (CM-MRT) based on MRT, combined with combined weighting and MWDM. Findings The effectiveness of the model is verified by a simulation experiment of a refueling mission. The results show that the proposed model has a high correlation with the subjective and objective workload data measured in the simulation experiments. Originality/value This paper provides an evaluation process of the workload of RA pilots in aerial refueling, which can evaluate the workload of pilots from four dimensions: visual, auditory, cognitive and psychomotor, and can dynamically describe the dynamic floating process of the workload through the MWMD model.

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Publication Details

Journal
Kybernetes
Published
2025-04-24
DOI
https://doi.org/10.1108/k-11-2024-3169
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

A prediction model of the mental workload of pilots based on improved multiple resource theory

Man Ding, Chuyi Zhang, Huining Pei, Xinyu Liu et al.
Kybernetes
Human-Automation Interaction and Safety
article

A prediction model of the mental workload of pilots based on improved multiple resource theory

Man Ding, Chuyi Zhang, Huining Pei, Xinyu Liu, Yujie Ma, Hao Gong
article en

Abstract

Purpose With the development of modern military technology, new combat equipment increased function-ality, and at the same time increased the workload of the operator. The goal of this study is to accurately and objectively predict the mental workload of the pilots of receiver aircraft (RA) during aerial refueling. Design/methodology/approach The prediction model is based on the multiple resource theory (MRT). Level-based weight as-sessment (LBWA) and the decision-making trial and evaluation laboratory–interpretative structural modeling (DEMATEL-ISM) method are used to determine the weights of mental resource channels in terms of importance and relevance, respectively, due to arithmetic accuracy and ability to analyze at multiple levels of hierarchy. Furthermore, the Mental Workload Dynamic Model (MWDM) was introduced to propose a Mental Workload Prediction Model (CM-MRT) based on MRT, combined with combined weighting and MWDM. Findings The effectiveness of the model is verified by a simulation experiment of a refueling mission. The results show that the proposed model has a high correlation with the subjective and objective workload data measured in the simulation experiments. Originality/value This paper provides an evaluation process of the workload of RA pilots in aerial refueling, which can evaluate the workload of pilots from four dimensions: visual, auditory, cognitive and psychomotor, and can dynamically describe the dynamic floating process of the workload through the MWMD model.

Kybernetes
Openalex Percentile: Top 91%
Human-Automation Interaction and Safety
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A prediction model of the mental workload of pilots based on improved multiple resource theory — Man Ding, Chuyi Zhang, et al. · Kybernetes (2025) | TGRS Research Map | TGRS