Autonomous path planning of departing aircraft in terminal area

With the gradual development of the aircraft self-separation operation and the continuous climbing operation (CCO) mode, it can effectively solve the problem that the departure path of aircraft in the current terminal area is fixed and single, which leads to the low operational efficiency of airspace. Therefore, an autonomous path planning method based on artificial potential field-particle swarm optimization（APF-PSO） algorithm was proposed in this paper. To guarantee operation safety, the airspace environment was first rasterized, the aircraft autonomous operation mode was taken into consideration, and the airspace complexity of each grid was computed. This prevented departing aircraft from flying into high-complexity grids. The aircraft climbing performance constraint model was constructed based on the BADA database and reduced force climbing mode. Then the path planning was carried out by using the APF-PSO algorithm of artificial potential field（APF） and particle swarm optimization（PSO） algorithm, and the local extremum-target unreachable problem inherent in the artificial potential field method was solved by using the region search algorithm of particle swarm optimization. The Bessel curve method was used to optimize the path planning and the concept of sliding time window was introduced to optimize the departure time of aircraft. Finally, using the actual structure and operation data of Shanghai terminal airspace, the proposed method was applied to simulate. The simulation test results show that the APF-PSO algorithm can effectively generate the aircraft conflict-free departure path and avoid busy airspace. The optimized path satisfies the aircraft climbing performance constraints and is better than the actual path (path length reduced by 23.78%, maximum turning rate reduced by 55.73%, maximum climbing rate reduced by 9.94%). Additionally, the autonomous operation mode of departing aircraft results in a more balanced airspace operation condition than the actual operating mode (a reduction of 3.92% in peak grid complexity), which can significantly increase the airspace utilization rate.