Overview
This editorial invites researchers to submit their work for a special issue titled “AI-Driven Innovations in Air Traffic Management and Aviation Safety”. This issue aims to highlight the transformative role of artificial intelligence (AI) and machine learning (ML) in enhancing the efficiency and safety of airspace operations. As the complexity of aviation data increases, the need for automated, data-driven solutions becomes critical for the future of aviation.
Background & Relevance
The integration of AI and ML into air traffic management is becoming increasingly important as the aviation sector faces new challenges. With the rise of new entrants in airspace and the growing volume of data, leveraging advanced technologies is essential for improving operational safety and resilience. This special issue will explore various applications of AI/ML, including decision support systems and the deployment of automated tools, which are crucial for modern aviation practices.
Key Details
- Submission Deadline: July 31, 2026
- Guest Editor: Dr. Milad Memarzadeh, NASA Ames Research Center
- Journal: Aerospace (Open Access)
- Impact Factor: 2.2
- CiteScore: 4.0
- Journal Link: Aerospace Special Issue
Eligibility & Participation
This call for papers is open to researchers and practitioners in the fields of AI, ML, and aviation. Contributions are encouraged from those who can integrate aviation expertise with advanced AI/ML methodologies to address current challenges in air traffic management and safety.
Submission or Application Guidelines
Interested authors should prepare their manuscripts in accordance with the journal’s submission guidelines. Manuscripts should focus on the application of AI/ML in aviation, covering topics such as:
– AI/ML for decision support
– Real-world deployment of automated tools
– Generative AI for managing unstructured data
– Responsible AI practices
– Verification and validation of AI/ML systems
– AI as a service in air traffic management
Additional Context / Real-World Relevance
The application of AI in aviation is not just a trend; it is a necessity for ensuring safety and efficiency in increasingly crowded airspaces. As the industry evolves, understanding how to responsibly implement these technologies will be crucial for the future of air travel. This special issue aims to gather insights that can guide the development of robust AI systems in aviation.
Conclusion
Researchers are encouraged to explore this opportunity to contribute to the advancement of AI in aviation. By submitting your work, you can play a vital role in shaping the future of air traffic management and safety. For further details, please refer to the journal’s website and prepare your submissions ahead of the deadline.
Category: CFP & Deadlines
Tags: ai, machine learning, aviation safety, air traffic management, deep learning, generative ai, automated tools, responsible ai
