With the increasing frequency of flight activities in low altitude airspace, flight conflicts between drones and the surrounding environment have become more apparent. To achieve the safe, standardized, and intelligent development of low altitude airspace, the identification and detection of drone flight conflicts in low altitude environments are crucial for achieving safety management. This article provides a comprehensive review of the latest developments in drone safety assurance technology in low altitude flight environments, with a particular focus on the two core areas of trajectory prediction and flight conflict detection. Firstly, a comprehensive comparative analysis was conducted on flight path prediction methods based on dynamic principles, state estimation techniques, and deep learning algorithms, and their respective strengths and weaknesses were explored in depth. Secondly, the article explores flight conflict detection methods using principles of bionics, machine learning techniques, and computer vision technology, emphasizing the effectiveness of these technologies in practical applications and the challenges they face. The article concludes with some forward-looking thoughts on the future development of safe flight technology for unmanned aerial vehicles.
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Geng, J., Chen,Y. (2025) A Review of Research on Low Altitude Airspace Unmanned Aerial Vehicle Flight Safety Assurance Technology. Scientific Research Bulletin, 2(3), 1-7.