Conflict Risk Assessment between Non-Cooperative Drones and Manned Aircraft in Airport Terminal Areas
Source abstract
Abstract
Recent years have seen an increase in events of drone incursion into airport terminal areas, leading to safety concerns and disruptions to airline operations. It is of great importance to identify the potential conflict, especially for those non-cooperative drones, as their intentions are always unknown. For the safe operation of air traffic, this paper proposes a conflict risk assessment method between non-cooperative drones and manned aircraft in the terminal area. First, the trajectory data of manned aircraft and drones are obtained. Real-time cylindrical protection zones are established around manned aircraft according to the separation interval for safe operation between the drone and the manned aircraft at different altitudes. Secondly, trajectory predictions for the manned aircraft and the drone are conducted, respectively. A quartile regression bidirectional gate recurrent unit neural network is proposed in this research for the trajectory prediction of the drones. The model integrates the bidirectional gated recurrent unit structure and the quartile regression structure. The performance indicators confirm the superiority of the proposed model. Based on the trajectory prediction results, it is then determined whether there is a conflict risk between the drone and manned aircraft by comparing the position distribution of the drone as well as the real-time cylindrical protection zone of the manned aircraft. The conflict probability between the drone and the manned aircraft is then calculated. The prediction accuracy of conflict probability is estimated by Monte Carlo simulation methods. The collision probability prediction accuracy of manned aircraft and drones at different flight stages and altitudes ranges from 73% to 97%, which shows the reliability of the proposed method. Finally, the collision probability between the drone and the manned aircraft at the closest encountering point and the estimated time to reach the closest encountering point are calculated. This paper predicts the conflict risk between the drone and manned aircraft, thus providing theoretical support for the safe operation of air transport in low-altitude environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Air Traffic Management and Optimization · Autonomous Vehicle Technology and Safety · Aerospace and Aviation Technology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Transportation, Southeast University, Nanjing 211189, China
CAUPD Beijing Planning & Design Consultants LTD, Nanjing 100044, China
College of General Aviation and Flight, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Funding
National Natural Science Foundation of China · Fundamental Research Funds for the Central Universities of China · Graduate Innovation Open Fund of Nanjing University of Aeronautics and Astronautics
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