Applied Sciences (Dec 2023)

Collaborative Allocation Method of En-Route Network Resources Based on Stackelberg Game Model

  • Wen Tian,
  • Xuefang Zhou,
  • Ying Zhang,
  • Qin Fang,
  • Mingjian Yang

DOI
https://doi.org/10.3390/app132413292
Journal volume & issue
Vol. 13, no. 24
p. 13292

Abstract

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To further enhance fairness in the allocation of en-route space–time resources in the collaborative trajectory selection program, a study on the plan preferences between air traffic control (ATC) and airlines in the selection process of the final plan is conducted based on the initial resource allocation plans, considering the roles of airlines in resources allocation decisions. By using Stackelberg game theory, a game model is established for the roles played by ATC and airlines in the process of selecting plans. Then, combining the overall consideration of ATC for all affected flights, the preferences of airlines for initial allocation plans are obtained, and the option range of selectable plans is narrowed down to determine the optimal allocation plan. The results of the example analysis show that the proposed model and method can effectively select the optimal allocation plan from the six initial allocation plans, select the trajectories and entry slots in the congestion areas for airlines that better meet the operation demand, and provide the decision basis with more preferences for ATC to select the final allocation plan. When ATC prefers the lowest overall delay cost, the delay cost of the selected optimal allocation plan is 267.7 min, which is 23.84% lower than the traditional RBS algorithm; when considering the preferences of the main base airline in East China, the delay cost of the selected optimal allocation plan is 287.7 min, which is 18.15% lower than the traditional RBS algorithm.

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