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.
LIU Jixin
,
JIANG Hao
,
DONG Xinfang
,
LAN Sijie
,
WANG Haozhe
. Dynamic collaborative sequencing method for arrival flights based on air traffic density[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020
, 41(7)
: 323717
-323717
.
DOI: 10.7527/S1000-6893.2020.23717
[1] 中国民用航空局. 2018年民航行业发展统计公报[R]. 北京:中国民用航空局, 2019. Civil Aviation Administration of China. Development statistics bulletin of civil aviation industry in 2018[R]. Beijing:Civil Aviation Administration of China, 2019(in Chinese).
[2] HU X B, CHEN W H. Receding horizon control for aircraft arrival sequencing and scheduling[J]. IEEE Transactions on Intelligent Transportation Systems, 2005, 6(2):189-197.
[3] HU X B, PAOLO E D. Binary-representation-based genetic algorithm for arrival sequencing and scheduling[J]. IEEE Transaction on Intelligent Transportation Systems, 2008, 9(2):301-310.
[4] HU X B, PAOLO E D. An efficient genetic algorithm with uniform crossover for air traffic control[J]. Computers & Operations Research, 2009, 36(1):245-259.
[5] 张启钱, 胡明华, 施赛锋. 基于RHC的航班着落调度多目标优化算法[J]. 南京航空航天大学学报, 2012, 44(3):393-398. ZHANG Q Q, HU M H, SHI S F. Multi-object optimization algorithm for aircraft landing based on receding horizon control strategy[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2012, 44(3):393-398(in Chinese).
[6] 王菲, 张军峰, 葛腾腾, 等. 基于分支定界的离场航空器动态排序[J]. 南京航空航天大学学报, 2015, 47(4):547-552. WANG F, ZHANG J F, GE T T, et al. Dynamic departure sequencing based on branch and bound algorithm[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2015, 47(4):547-552(in Chinese).
[7] 张军峰, 王菲, 葛腾腾. 基于分支定界法的进场航空器动态排序与调度[J]. 系统仿真学报, 2016, 28(8):1909-1914. ZHANG J F, WANG F, GE T T. Dynamic arrival sequencing & scheduling based on branch & bound algorithm[J]. Journal of System Simulation, 2016, 28(8):1909-1914(in Chinese).
[8] 王菲. 多跑道机场进离场航空器协同排序研究[D]. 南京:南京航空航天大学, 2016. WANG F. Research on collaborative sequencing of arrival and departure aircrafts in multi-runway airport[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2016(in Chinese).
[9] 马园园, 胡明华, 张洪海, 等. 多机场终端区进场航班协同排序方法[J]. 航空学报, 2015, 36(7):2279-2290. MA Y Y, HU M H, ZHANG H H, et al. Optimized method for collaborative arrival sequencing and scheduling in metroplex terminal area[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(7):2279-2290(in Chinese).
[10] 马园园, 胡明华, 尹嘉男, 等. 多机场终端区进离场交通流协同排序方法[J]. 航空学报, 2017, 38(2):225-237. MA Y Y, HU M H, YIN J N, et al. Collaborative sequencing and scheduling method for arrival and departure traffic flow in multi-airport terminal area[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(2):225-237(in Chinese).
[11] 葛腾腾. 多机场终端空域进离场协同调度研究[D]. 南京:南京航空航天大学, 2017. GE T T. Research on collaborative scheduling of arrival and departure aircrafts in multi-airport terminal area[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2017(in Chinese).
[12] 张军峰, 葛腾腾, 郑志祥. 多机场终端区进离场航班协同排序研究[J]. 交通运输系统工程与信息, 2017, 17(2):197-204. ZHANG J F, GE T T, ZHENG Z X. Collaborative arrival and departure sequencing for multi-airport terminal area[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(2):197-204(in Chinese).
[13] SALEHIPOUR A, MODARRES M, NAENI L M. An efficient hybrid meta-heuristic for aircraft landing problem[J]. Computers & Operations Research, 2013, 40:207-213.
[14] ZHAN Z H, ZHANG J, LI Y, et al. An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and schedule problem[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(2):399-412.
[15] GULSAH H, GHAITH R, AMEER H A, et al. Greedy algorithms and metaheuristics for a multiple runway combined arrival-departure aircraft sequencing problem[J]. Journal of Air Transport Management, 2013, 32:39-48.
[16] CAO Y, RATHINAM S, SUN D F. Greedy-heuristic-aided mixed-integer linear programming approach for arrival scheduling[J]. Journal of Aerospace Information Systems, 2013, 10(7):323-336.
[17] PINOL H, BEASLEY J E. Scatter search and bionomic algorithms for the aircraft landing problem[J]. European Journal of Operational Research, 2006, 171:439-62.
[18] 中国民用航空局. 民用航空空中交通管理规则:CCAR-93-R5[S]. 北京:中国民用航空局, 2018. Civil Aviation Administration of China. Civil aviation air traffic management rules:CCAR-93-R5[S]. Beijing:Civil Aviation Administration of China, 2018(in Chinese).
[19] 中国民用航空局. 民航航班正常统计办法:CCAR-93-R5[S]. 北京:中国民用航空局, 2012. Civil Aviation Administration of China. Measures for normal statistics of civil aviation flights:CCAR-93-R5[S]. Beijing:Civil Aviation Administration of China, 2012(in Chinese).
[20] 赵嶷飞, 陈凯, 刘刚, 等. 一种新的扇区拥挤告警指标及应用[J]. 中国安全科学学报, 2009, 19(3):103-107. ZHAO Y F, CHEN K, LIU G, et al. A new flow alert index for sector congestion and its application[J]. China Safety Science Journal, 2009, 19(3):103-107(in Chinese).
[21] DE JONG K A. An analysis of the behavior of a class of genetic adaptive systems[D]. Michigan:University of Michigan, 1975.
[22] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multi-objective genetic algorithm:NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2):182-197.