Comprehensive Evaluation of Remote Tower Controllers’ Situation Awareness Level Based on the Entropy Weight Method (EWM)–TOPSIS–Gray Relational Analysis Model

In recent years, the rapid development of remote tower technology has made it crucial to accurately assess the situational awareness (SA) levels of remote tower controllers. Such an assessment is significant for controller training and remote tower system design. This study employed the SART scale to compare controllers’ SA scores in traditional and remote tower environments. Results revealed significant differences, especially in attention demand and situational understanding. Subsequently, a quantitative analysis of controllers’ perception, understanding, and decision-making abilities was conducted, integrating subjective and objective data. Eye-tracking, heart rate, working memory scales, and communication-coordination scales showed significant results. Experienced controllers had better psychological safety skills, while trainees were more likely to increase vigilance. Moreover, a series of sensitive SA indicators were identified. An evaluation index system was established using the entropy weight method. By calculating the Euclidean distance, Gray relational degree, and comprehensive proximity coefficient, the SA levels of controllers were comprehensively evaluated. The top five important indicators were average blink rate, scan length, average fixation duration, fixation duration, and average pupil diameter. These findings support enhancing air traffic control safety and refining SA assessment for remote tower controllers.

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Publication Details

Journal
Applied Sciences
Published
2025-02-28
DOI
https://doi.org/10.3390/app15052623
Citations
1
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
1.40
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article

Comprehensive Evaluation of Remote Tower Controllers’ Situation Awareness Level Based on the Entropy Weight Method (EWM)–TOPSIS–Gray Relational Analysis Model

Hao Miao, Zhaoning Zhang, Tingting Lu
1 citations
Applied Sciences
Risk and Safety Analysis
1.40
article

Comprehensive Evaluation of Remote Tower Controllers’ Situation Awareness Level Based on the Entropy Weight Method (EWM)–TOPSIS–Gray Relational Analysis Model

Hao Miao, Zhaoning Zhang, Tingting Lu
article en
1 citations

Abstract

In recent years, the rapid development of remote tower technology has made it crucial to accurately assess the situational awareness (SA) levels of remote tower controllers. Such an assessment is significant for controller training and remote tower system design. This study employed the SART scale to compare controllers’ SA scores in traditional and remote tower environments. Results revealed significant differences, especially in attention demand and situational understanding. Subsequently, a quantitative analysis of controllers’ perception, understanding, and decision-making abilities was conducted, integrating subjective and objective data. Eye-tracking, heart rate, working memory scales, and communication-coordination scales showed significant results. Experienced controllers had better psychological safety skills, while trainees were more likely to increase vigilance. Moreover, a series of sensitive SA indicators were identified. An evaluation index system was established using the entropy weight method. By calculating the Euclidean distance, Gray relational degree, and comprehensive proximity coefficient, the SA levels of controllers were comprehensively evaluated. The top five important indicators were average blink rate, scan length, average fixation duration, fixation duration, and average pupil diameter. These findings support enhancing air traffic control safety and refining SA assessment for remote tower controllers.

Applied SciencesVol. 15(5)
Civil Aviation University of China (CN)
Openalex Percentile: Top 18%
Risk and Safety Analysis
1.40
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Comprehensive Evaluation of Remote Tower Controllers’ Situation Awareness Level Based on the Entropy Weight Method (EWM)–TOPSIS–Gray Relational Analysis Model — Hao Miao, Zhaoning Zhang, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS