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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2020, Vol. 41 ›› Issue (7): 323717-323717.doi: 10.7527/S1000-6893.2020.23717

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Dynamic collaborative sequencing method for arrival flights based on air traffic density

LIU Jixin1,2, JIANG Hao1,2, DONG Xinfang1,2, LAN Sijie1,2, WANG Haozhe3   

  1. 1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
    2. National Key Laboratory of Air Traffic Flow Management, Nanjing 211106, China;
    3. Air Traffic Management Bureau of Tianjin Civil Aviation Administration, Tianjin 300300, China
  • Received:2019-12-08 Revised:2020-02-07 Online:2020-07-15 Published:2020-04-10

Abstract: To meet the needs of Collaborative Decision Making (CDM), dynamic collaborative sequencing of arrival flights is systematically studied, considering the demands of air traffic control units, airlines and airports. A dynamic sequencing method for arrival flights is designed, a slot exchange method is proposed, and a collaborative sequencing model based on air traffic density is built. A genetic algorithm with the elitist reservation and a fast non-dominated sorting genetic algorithm with the elitist strategy are designed to achieve the optimal solution of dynamic collaborative sequencing of arrival flights. Compared with those of the Receding Horizon Control (RHC) method, the results of the dynamic collaborative method are independent of the start time of sequencing with the required sequencing times reduced by 26.4% on average, leading to higher sequencing efficiency. Compared with that of the First Come First Service (FCFS) method, under the condition of high density, the landing time of the last arrival flight in each sequencing stage is 199.8 s ahead of schedule on average with the dynamic collaboration method; under the condition of medium density, the total flight delay of each sequencing stage is reduced by 29.9% on average, while the flight delay equilibrium is increased by 34.4% on average; under the condition of low density, with the premise that the punctuality rate of arrival flights and the fairness of flight delays are guaranteed, one sequencing mode of arrival flights is added if the sequencing stage satisfies the slot exchange rules. The proposed method can optimize the sequencing of arrival flights, significantly enhancing the runway capacity and effectively improving the flight delay equilibrium and fairness. In line with the concept of collaborative decision making, this method can achieve collaborative sequencing of ATC, airlines and airports.

Key words: air traffic control, collaborative decision making, arrival sequencing, slot exchange, multi-objective optimization, genetic algorithm

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