Ergonomics Considerations in Air Traffic Conflict Detection and Resolution

Trapsilawati, Fitri; Li, Fan; Yisi, Liu · 2023 · International Journal of Technology

DOI: 10.14716/ijtech.v14i4.5908

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Summary

This systematic literature review addresses the ergonomic challenges in air traffic conflict detection and resolution (CDR) amidst the post-pandemic surge in global air traffic density. Motivated by the need to ensure safety as aviation recovers, the study identifies a gap in existing research, which predominantly focuses on algorithmic models rather than the human factors affecting air traffic controllers (ATCOs). The authors aim to develop a theoretical framework that integrates ergonomic considerations into the CDR process, treating air traffic control as a complex sociotechnical system. The study employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to select relevant literature. Initial searches in the Scopus database and other sources yielded 87 records published between 1973 and 2022. After screening for recency, availability, and relevance to human factors in ATC (excluding studies focused solely on algorithms, hardware, or pilots), 35 papers were included in the final analysis. The review synthesizes findings across four key elements of the sociotechnical system: humans, environment, interface/system, and task. The findings highlight specific ergonomic issues within each domain. Regarding human factors, expertise influences control strategies, though semantic alert designs and scan-path training can mitigate performance gaps between novices and experts. Trust in automation is critical; excessive trust leads to complacency and reduced situation awareness, while insufficient trust causes operators to ignore aids. Gender differences were noted in physiological responses to workload, though not in overall CDR performance. Environmental factors such as crosswinds, traffic density, and conflict geometry significantly increase mental workload and reduce tracking performance. Interface and system issues reveal that while automation aids like Multi-Conflict Displays improve detection, complex displays like trajectory predictions can increase workload. Alerting designs combining auditory, semantic, and visual features were found most effective. Task-based analysis indicates that decision-making tasks impose higher cognitive demands than routine monitoring, and night shifts exacerbate stress and fatigue. The significance of this study lies in its proposed framework, which underscores the necessity of designing ATC systems that foster appropriate trust and automation transparency. The authors conclude that future research must prioritize accelerating ATCO proficiency, designing systems that induce sufficient trust, analyzing global traffic patterns rather than just density, and improving human-automation collaboration. These directions are essential for enhancing air traffic safety and efficiency as global flight volumes continue to rise.

Key finding

A theoretical framework modeling air traffic control as a sociotechnical system was developed, identifying human, environmental, interface, and task factors as critical determinants of conflict detection and resolution performance.

Methodology

review

Sample size: 35

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-15; verification: verified.

Topics

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• automation