Flight Conflict Resolution Method Based on Hybrid Differential Evolution and Rat Swarm Optimizer
Year: 2025
Type: article
Abstract: ObjectiveWith the steady improvement of China's economy, the civil aviation transportation industry continues to recover, and the increasing demand for travel results in a rapid increase in air traffic flow. However, given the limitation of airspace resources, the increase in the number of aircraft inevitably raises the risk of flight conflicts. Therefore, research on flight conflict resolution becomes crucial, and an efficient and reliable conflict resolution method remains essential to address this issue. Two main shortcomings exist in current research on conflict resolution methods: 1) The commonly used conflict resolution methods exhibit low solution accuracy and slow convergence speed, which limit their applicability across different conflict scenarios. 2) The resolution strategies are overly singular, with most studies focusing solely on heading adjustment without sufficient consideration of composite adjustment strategies that integrate heading and speed. Differential Evolution (DE), a population-based global stochastic search algorithm, possesses a simple structure, strong global optimization performance, robust adaptability, and good scalability, making it a feasible solution for global optimization problems such as flight conflict resolution. However, DE exhibits slow search speed, low convergence accuracy, and a tendency to fall into local optima in multi-aircraft conflict resolution problems, which restricts its practicality. Rat Swarm Optimizer (RSO), a novel heuristic algorithm that simulates rat behaviors of chasing and fighting prey, features a simple structure, few regulation parameters, and fast convergence speed and can effectively compensate for DE's limitations. Based on this, the present study combines the advantages of DE and RSO to propose a hybrid algorithm (HDERSO) and applies it to the problem of flight conflict resolution.MethodsHDERSO incorporates the search mechanism of RSO into DE and utilizes a selection probability to adaptively control the generation strategies for offspring individuals at different evolutionary stages. This approach provides directional guidance for the evolution process and avoids blind or ineffective searching. In the early evolutionary stage, the algorithm emphasizes the global exploration capability of DE to search the solution space thoroughly, discover promising regions, and reduce the risk of premature convergence. In the middle and later stages, HDERSO uses the local exploitation ability of RSO to accelerate optimization and enhance convergence accuracy. In addition, control parameters such as the scaling factor and crossover probability influence the quality of DE's offspring individuals. Typically, these parameters require appropriate adjustments during population evolution. Accordingly, HDERSO applies the control parameters to each individual and adaptively generates them by tracking the states of the population and individuals in real-time, improving optimization performance and algorithm applicability.Results and DiscussionsThe performance of HDERSO is evaluated using the IEEE CEC2017 test set comprising 29 functions with diverse features (2 unimodal functions, seven multimodal functions, 10 hybrid functions, and 10 composition functions). The mean and standard deviation of the optimal solutions obtained by HDERSO and the comparative algorithms are statistically analyzed using Wilcoxon and Friedman tests at the 5% significance level. The experimental results demonstrate that the proposed HDERSO achieves higher solution quality and faster convergence speed. Aircraft involved in flight conflict require feasible resolution trajectories based on conflict resolution methods combined with specific strategies, which lead to certain positional offsets from the planned trajectories. Larger positional offsets result in greater flight delays and increased fuel consumption. A flight conflict resolution model based on minimizing the trajectory offset is constructed, and resolution strategies involving heading adjustment, speed adjustment, and composite adjustment are designed. In addition, three typical flight scenarios with varying conflict characteristics (same-direction intersection, vertical intersection, and opposing head-to-head) are developed, and the proposed HDERSO is used in conflict resolution experiments. The results show that HDERSO resolves conflicts using all three strategies in the same-direction intersection scenario. However, in opposing head-to-head scenarios, HDERSO fails to resolve conflicts using speed adjustment alone but successfully resolves them using heading adjustment and composite adjustment. HDERSO effectively resolves conflicts among multiple aircraft by applying different resolution strategies while maintaining the minimum flight safety interval. The results show that the proposed algorithm produces significantly smaller trajectory offsets and target fitness values across various conflict scenarios compared to other algorithms. The evolution curves further confirm that HDERSO is more competitive in convergence speed and solution accuracy, achieving higher accuracy within 250 generations. In addition, the prioritization of the three conflict resolution strategies (heading adjustment, speed adjustment, and composite adjustment) is analyzed based on scenario applicability, solution quality, and operational complexity. The results indicate that in terms of scenario applicability, composite adjustment and heading adjustment outperform speed adjustment; in terms of solution quality, speed adjustment is superior, followed by composite adjustment and heading adjustment; in terms of operational complexity, the strategies are prioritized as heading adjustment, speed adjustment, and composite adjustment.ConclusionsAccordingly, the proposed HDERSO is an effective and feasible conflict resolution method that plans optimal resolution trajectories for different flight scenarios, reducing fuel consumption and minimizing flight costs. The outcomes of this study provide a valuable reference for air traffic control departments in implementing flight conflict resolution measures.
Authors: WANG Shihao, LI Yuzhen, XIONG Qibing, YANG Hongyu
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7009945764
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