This research employs multi-objective optimization to improve flight path planning, indicating effective traffic congestion relief in Terminal Areas.
With the continuous growth of air transportation demand, air traffic congestion in the Terminal Area has become increasingly serious. In order to assist controllers in efficiently alleviating the traffic congestion situation in the Terminal Area, this paper takes aircraft trajectory adjustment and flow control from the perspective of the Terminal Area as a starting point and proposes a congestion relief strategy based on a complex network and multi-objective optimization theory. First, a Terminal Area traffic network model is established with the approach point, departure point, waypoint, and navigation station as nodes and the flight path as edges. Next, a multi-objective optimization model that takes into account both congestion relief and reduced operating costs is constructed. Finally, an improved ant colony optimization is proposed to solve this optimization model and provide a unified approach to path planning for multiple aircraft. Finally, simulation experiments were conducted based on the airspace structure and operation of the Beijing Terminal Area. At the same time, ablation experiments were designed to compare the method in this paper with other ant colony optimizations. The experimental results show that the path planning results of the improved ant colony optimization can better alleviate the traffic congestion situation in the Terminal Area, converge faster, and reduce the risk of falling into a local optimum.
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Ji et al. (2025) studied this question.
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