The use of artificial intelligence in air traffic control: a theoretical review

Abstract

Aviation is a growing industry critical to commercial and military operations worldwide. This growth brings with it more complex and intensive air traffic management requirements. Air traffic control is a critical service operating within airports and airspace to ensure aircraft's safe, efficient and orderly routing. However, as the traffic density in the airspace increases, human operators are more likely to make mistakes and existing air traffic management systems may be inadequate. At this point, applying artificial intelligence (AI) technologies in air traffic control offers a significant innovation to the sector. This paper examines how AI technologies are used in air traffic control. The opportunities offered by technologies such as machine learning, deep learning, unmanned aerial vehicles (UAVs) and blockchain in air traffic control are discussed, and the role of these technologies in reducing human errors, increasing efficiency and optimizing decision-making processes is discussed. In particular, the integration of UAVs into the airspace and the contributions of AI in managing this process were emphasized. In addition, the benefits of blockchain technology in terms of data security and traceability are evaluated.