关键词: 航空运输, 空中交通复杂度, 改进A*算法, 空域, 线性动力系统, 空中交通管理

Abstract: Traditional trajectory optimization methods often encounter challenges in enhancing local flight efficiency while maintaining the overall stability of airspace operations. To address this issue, this paper introduces a multifaceted complexity calculation method specifically designed for airspace grid assessment and explores its application in trajectory search algorithms. Initially, interaction complexity is computed based on two motion tendencies: "approaching" and "converging", while background complexity is derived from airspace structure and meteorological conditions. Subsequently, these complexities are allocated to airspace grids, forming a complexity map of each grid. Finally, this method is integrated to an improved trajectory optimization approach to assess the impact of optimization results on airspace operational pressure. Validation is conducted through simulations in a modeled airspace and actual data from the Shanghai Terminal Area. Simulation results indicate that the operational pressure of air traffic scenarios can be quantified by multifaceted complexity. Compared to the original data, the complexity-assessed improved A* algorithm results in a 20.10% reduction in flight distance, an estimated 30.00% decrease in flight time, and a 16.67% reduction in maneuvers. Furthermore, when comparing with original data and traditional A* algorithm optimized trajectories, the optimized results demonstrate a decrease in local airspace operational pressure.

Key words: air transportation, air traffic complexity, improved A* algorithm, airspace, linear dynamic system, air traffic management