Optimization of Lateral Collision Risk of Aircraft Based on the Skid-Slip Event Model

• Published in: International Journal of Aerospace Engineering Vol. 2022; pp. 1 - 11
• Main Authors: Liu, Hao, Zhu, Daiwu, Xie, Xiaofan, Chen, Jiuhao, Liu, Xiaokang
• Format: Journal Article
• Language: English
• Published: New York Hindawi 15.07.2022; John Wiley & Sons, Inc; Wiley
• Subjects: Aerospace engineering; Aircraft; Aircraft performance; Airspace; Algorithms; Conflict management; Curvature; Electronics in navigation; Error reduction; Kalman filters; Mathematical models; Navigation systems; Optimization; Risk assessment; Route planning; Smoothness; Software; Software development tools; China
• DOI: 10.1155/2022/2002423
• ISSN: 1687-5966

With the development of aircraft flow under the existing airspace capacity now, the shortage of airspace resources and flight delays have become significantly severe. Therefore, building a safe and efficient mathematical model from quantitative analysis and improving the scientificity of route planning and management are essential propositions for future research on new navigation systems. Based on the traditional event collision risk assessment model, the collision module is upgraded to an ellipsoid according to the performance of aircraft, integrating the boundary curvature optimization characteristics of the TSRRT (task-space rapidly-exploring random trees) algorithm. An aircraft event lateral conflict resolution model based on the TSRRT algorithm is proposed. Taking the A320 aircraft and 737-800 aircraft as experimental subjects, the corresponding collision coefficients are imported into software tools for the simulation and the Kalman filtering is combined to verify the smoothness of the front and rear boundary curvatures. The result proves that the event side collision risk of aircraft based on TSRRT is 15% of the traditional event model and the smooth curvature error is reduced by 80% due to the improvement. Therefore, the improved event model is practical and valuable, providing a theoretical basis for future track-based operations.