Preventing the Unpredictable: An Integrated Human Factors Approach to Reducing Aviation Accidents in the Era of Advanced Flight Technology

Advanced flight technology has made aviation safer, more capable, and more information-rich, yet it has not removed the human factor from accident causation. Modern cockpits, avionics suites, automation modes, flight management systems, electronic checklists, traffic alerting systems, weather products, and data-driven safety tools can strengthen pilot performance when they are understood and managed properly. However, the same technologies can also introduce new forms of complexity: mode confusion, automation complacency, data overload, alert fatigue, degraded manual-flying proficiency, and mismatches between cockpit information and crew mental models. This paper develops an integrated human factors framework for reducing aviation accidents in technology-rich operations. The study uses public aviation safety evidence, including NTSB accident data availability, Kaggle/NTSB-derived accident datasets, FAA aeronautical decision-making and instructor guidance, IATA 2024 contributing-factor statistics, ICAO 2025 safety reporting, and Boeing commercial jet accident summaries. It then develops a risk-scoring and training-analytics model that links human factors domains to operational phases, advanced technology contexts, and competency-based training interventions. Because personally identifiable flight-training records are not publicly available, the model uses a public-data-informed synthetic training observation layer to demonstrate how flight schools and operators can transform safety signals into non-punitive early-warning interventions. The findings show that the highest-priority risk intersections arise around approach, landing/go-around, abnormal events, automation mode awareness, manual flight-path control, SOP discipline, situational awareness, and weather-threat management. The paper concludes that aviation safety in the advanced technology era should be governed through integrated human factors controls, data-informed scenario training, safety management feedback loops, explainable risk scoring, and recurrent training that treats technology as a human-machine team member rather than a substitute for disciplined airmanship.

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Publication Details

Journal
Iconic Research and Engineering Journals
Published
2026-06-30
DOI
https://doi.org/10.64388/irev9i12-1719259
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Preventing the Unpredictable: An Integrated Human Factors Approach to Reducing Aviation Accidents in the Era of Advanced Flight Technology

Munashe Naphtali Mupa, Okebu Daniel Tobechukwu Chukwuemeka
Iconic Research and Engineering Journals
Human-Automation Interaction and Safety
article

Preventing the Unpredictable: An Integrated Human Factors Approach to Reducing Aviation Accidents in the Era of Advanced Flight Technology

Munashe Naphtali Mupa, Okebu Daniel Tobechukwu Chukwuemeka
article en

Abstract

Advanced flight technology has made aviation safer, more capable, and more information-rich, yet it has not removed the human factor from accident causation. Modern cockpits, avionics suites, automation modes, flight management systems, electronic checklists, traffic alerting systems, weather products, and data-driven safety tools can strengthen pilot performance when they are understood and managed properly. However, the same technologies can also introduce new forms of complexity: mode confusion, automation complacency, data overload, alert fatigue, degraded manual-flying proficiency, and mismatches between cockpit information and crew mental models. This paper develops an integrated human factors framework for reducing aviation accidents in technology-rich operations. The study uses public aviation safety evidence, including NTSB accident data availability, Kaggle/NTSB-derived accident datasets, FAA aeronautical decision-making and instructor guidance, IATA 2024 contributing-factor statistics, ICAO 2025 safety reporting, and Boeing commercial jet accident summaries. It then develops a risk-scoring and training-analytics model that links human factors domains to operational phases, advanced technology contexts, and competency-based training interventions. Because personally identifiable flight-training records are not publicly available, the model uses a public-data-informed synthetic training observation layer to demonstrate how flight schools and operators can transform safety signals into non-punitive early-warning interventions. The findings show that the highest-priority risk intersections arise around approach, landing/go-around, abnormal events, automation mode awareness, manual flight-path control, SOP discipline, situational awareness, and weather-threat management. The paper concludes that aviation safety in the advanced technology era should be governed through integrated human factors controls, data-informed scenario training, safety management feedback loops, explainable risk scoring, and recurrent training that treats technology as a human-machine team member rather than a substitute for disciplined airmanship.

Iconic Research and Engineering JournalsVol. 9(12)
Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Human-Automation Interaction and Safety
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