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<p>As aviation advances toward greater automation and data integration, human-centered design, regulatory alignment, and collaborative autonomy remain critical. This paper examines the integration of human-centric intelligent systems through three domains: artificial cognitive systems (ACS) in fatigue risk management, AI-supported accident investigation, and immersive mixed-reality (MR) training for eVTOL pilots. In fatigue risk management, ACS tools leverage real-time biometric data and predictive algorithms to provide adaptive recommendations aligned with International Civil Aviation Organization’s (ICAO) Doc 9966 and Federal Aviation Administration’s (FAA)/European Union Aviation Safety Agency (EASA) regulations. AI-enhanced investigation methods, incorporating models such as HFACS, STAMP-STPA, and BowTie, enable systemic risk analysis, scenario reconstruction, and early hazard detection while maintaining human oversight. In pilot training, immersive MR platforms, integrated with AI, offer adaptive, high-fidelity environments that accelerate skill acquisition for emerging AAM operations. The proposed Human–Intelligent Systems Integration (HISI) framework is conceived as a comprehensive model that places human expertise at its core, while incorporating adaptive forms of intelligence to enhance decision-making in complex environments. It is built upon the main three key pillars: alignment with regulatory expectations, operational transparency, and a culture of ongoing learning—ensuring that human judgement remains central even as intelligent systems evolve alongside. Strategic recommendations are provided for researchers, regulators, and industry stakeholders to ensure that future intelligent systems enhance, rather than replace, human capability in safety–critical aviation contexts.</p>

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Designing human-centric intelligent systems in aviation: applications of artificial cognitive systems, AI-enhanced investigations, and immersive eVTOL simulation training

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月6日

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  • Dimitrios Ziakkas,
  • Debra Henneberry,
  • Anastasios Plioutsias

摘要

As aviation advances toward greater automation and data integration, human-centered design, regulatory alignment, and collaborative autonomy remain critical. This paper examines the integration of human-centric intelligent systems through three domains: artificial cognitive systems (ACS) in fatigue risk management, AI-supported accident investigation, and immersive mixed-reality (MR) training for eVTOL pilots. In fatigue risk management, ACS tools leverage real-time biometric data and predictive algorithms to provide adaptive recommendations aligned with International Civil Aviation Organization’s (ICAO) Doc 9966 and Federal Aviation Administration’s (FAA)/European Union Aviation Safety Agency (EASA) regulations. AI-enhanced investigation methods, incorporating models such as HFACS, STAMP-STPA, and BowTie, enable systemic risk analysis, scenario reconstruction, and early hazard detection while maintaining human oversight. In pilot training, immersive MR platforms, integrated with AI, offer adaptive, high-fidelity environments that accelerate skill acquisition for emerging AAM operations. The proposed Human–Intelligent Systems Integration (HISI) framework is conceived as a comprehensive model that places human expertise at its core, while incorporating adaptive forms of intelligence to enhance decision-making in complex environments. It is built upon the main three key pillars: alignment with regulatory expectations, operational transparency, and a culture of ongoing learning—ensuring that human judgement remains central even as intelligent systems evolve alongside. Strategic recommendations are provided for researchers, regulators, and industry stakeholders to ensure that future intelligent systems enhance, rather than replace, human capability in safety–critical aviation contexts.