Banca de QUALIFICAÇÃO: LUCAS DE OLIVEIRA MORAIS

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : LUCAS DE OLIVEIRA MORAIS
DATE: 13/12/2024
TIME: 10:00
LOCAL: Virtual
TITLE:

Artificial Intelligence in Pilot-Centered Aviation: Redefining Systems and Human Collaboration

PAGES: 56
BIG AREA: Outra
AREA: Tecnologia e Inovação
SUMMARY:

Artificial Intelligence (AI) is reshaping aviation by enhancing operational efficiency, improving decision-making processes, and reducing human error through technologies like machine learning, deep learning, and autonomous systems. However, integrating these capabilities into aviation brings unique challenges, particularly in meeting the industry's rigorous safety and reliability standards. Traditional systems engineering approaches are insufficient to handle the adaptive and probabilistic nature of AI, and poorly designed implementations risk increasing pilot workload, diminishing situational awareness, and eroding trust in automation. These issues underline the necessity of a human-centered framework that aligns AI functionality with operational needs.

This research seeks to address these gaps by developing a systems engineering framework for AI integration that prioritizes both technical considerations and human factors. Specifically, the study examines the following questions: (1) What are the distinctive systems engineering challenges associated with AI in aviation? (2) How does AI influence critical human factors like workload, situational awareness, and decision-making? (3) What strategies can be employed to foster effective collaboration between pilots and AI systems?

The study employs a structured methodology comprising three phases. First, a use case and stakeholder analysis is conducted to identify operational contexts and key requirements. The second phase uses agent-based modeling and simulation, coupled with experimental designs, to evaluate the impact of AI on human-machine interactions under varying conditions. The final phase synthesizes findings to refine a human-centered framework that integrates AI technologies effectively.

This research aims to deliver a validated framework that incorporates iterative design, supports intuitive human-machine interfaces, and encourages early pilot involvement in system development. The outcomes are designed to guide industry stakeholders and regulatory authorities in implementing AI systems that enhance aviation safety, efficiency, and collaboration while addressing human-centric challenges. This study contributes not only to the safe integration of AI into aviation but also to the broader field of human-centered design for complex systems.

COMMITTEE MEMBERS:
Presidente - Interno ao Programa - 1763439 - LUCIANA PEREIRA
Membro Titular - Examinador(a) Externo à Instituição - MOACYR MACHADO CARDOSO JÚNIOR
Membro Titular - Examinador(a) Externo à Instituição - MARCUS RÖSTH
Membro Suplente - Examinador(a) Interno ao Programa - 236.927.878-12 - ANDERS PETTER KRUS - Linköping Un
Membro Suplente - Examinador(a) Externo à Instituição - RAGHU CHAITANYA - Linköping Un
Membro Suplente - Examinador(a) Externo à Instituição - RICARDO JOSÉ NUNES DOS REIS - EMBRAER