TITLE: ATFM AI solutions to prevent airspace congestions
AUTHORS: Muharem Šabić, Šeila Šumar, Amer Kurešepi
ABSTRACT: The aviation industry’s growth has strained air traffic management systems, causing congestion and safety risks. Efficient solutions are needed to manage the increasing flight demand. Artificial intelligence (AI) and data analytics offer promising improvements for air traffic flow management and operations optimization. Air traffic flow management (ATFM) is the most important for ensuring the safe and efficient operation of airspace. Unexpected events can lead to congestion so this paper examines the application of artificial intelligence (AI) to mitigate air space congestion. AI can improve the effectiveness of ATFM strategies and manage air flow in various situations such as adverse weather conditions, technical issues, and unexpected delays.AI technologies allow for the rapid analysis of large amounts of data in real-time to identify trends and predict future scenarios. This enables air traffic controllers and dispatchers to make informed decisions in critical situations and prevent airspace congestion. Furthermore, AI solutions enable the optimization of flight paths to reduce congestion and minimize time spent in airspace. This is not only beneficial for reducing costs and CO2 emissions but also for improving the passenger experience by reducing delays and optimizing flight times.
KEYWORDS: Artificial intelligence (AI), Data analytics, Air traffic flow management (ATFM), Congestion mitigation, Machine Learning, Solutions
PAGES: 112-121
DOI: