A Multiaircraft Path Distributive Planning Method via Autonomous Self‐Separation Operation Mode
Ruiying Wen, Jiaxing He, Yupeng Guo, Hongyong Wang · Journal of Advanced Transportation · 2025
In this paper, a multiaircraft path planning method framework for autonomous operation and distributed decision‐making was proposed. The core content of this framework consists of two parts: single‐aircraft path planning and multiaircraft path coordination. The path planning process includes airspace operational situation assessment, initial path generation based on operational situation, path optimization, and smoothing. A joint path planning algorithm of artificial potential field (APF) and particle swarm optimization is designed to overcome the inherent defects of the APF method and optimize the path to make it more resistant to disturbance. In the process of multiaircraft route coordination, a mixed strategy game model is constructed to promote the fair allocation of airspace resources among aircraft. The mathematical properties of the mixed strategy Nash equilibrium solution for this problem are presented. Finally, a simulation scenario is constructed based on the actual sector structure (ZSSSAR01) and running data to verify the effectiveness of the proposed method. The simulation results show that with the increasing proportion of aircraft operating in the autonomous mode, the length of the planned path increases first and then decreases, the airspace operation situation is gradually balanced in the spatial distribution, and the robustness of the planned path is gradually enhanced. The average path length of aircraft increases only by 9.15%, but the peak air traffic complexity can be reduced by 34.77%, and the number of highly utilized grids in airspace can be increased by 22.55%. And, the anti‐disturbance capability of this path is significantly improved. It proves that the multiaircraft distributed route planning method proposed in this paper has a good application prospect in future air traffic management.