首页|期刊导航|南京航空航天大学学报(英文版)|容量不确定性下空中交通流量管理的需求与容量平衡

容量不确定性下空中交通流量管理的需求与容量平衡OACSTPCD

Stochastic Air Traffic Flow Management for Demand and Capacity Balancing Under Capacity Uncertainty

中文摘要英文摘要

引入了一种创新方法,实现了协同空中交通流量管理框架下扇区容量不确定性的需求与容量平衡.受极端天气、空军活动、管制员工作负荷等不可忽视的隐性因素影响,空域容量具有不确定性,进而影响流量管理优化结果.本文重点研究了扇区容量不确定性对需求与容量平衡优化,以及对空中交通流量管理优化的影响.在协同流量管理框架下实施多种策略,如延误指派和改航绕飞等管理交通流.进而提出了一种场景优化方法解决扇区容量的不确定性.结果显示,所提方法可以实现更好的需求与容量的平衡,并在空中交通流量管理问题中得到近似最优解,解决大规模的流量优化实例(24 h下的7个容量场景,6 255个航班以及8 949条航迹)只需要5~15 min.本文实验计算是已知的首次在协同流量管理框架下解决大规模随机性空中交通流量管理问题的有效实例.

This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6 255 flights and 8 949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.

陈运翔;许炎;赵嶷飞

武汉大学电子信息学院,武汉 430072,中国英国克兰菲尔德大学航空、交通与制造学院,贝德福德 MK430AL,英国武汉大学电子信息学院,武汉 430072,中国||中国民航大学空中交通管理学院,天津 300300,中国

空中交通流量管理需求与容量平衡航班延误扇区容量不确定性地面等待场景决策树

air traffic flow managementdemand and capacity balancingflight delayssector capacity uncertaintyground delay programsprobabilistic scenario trees

《南京航空航天大学学报(英文版)》 2024 (5)

656-674,19

This work was partially funded by the China Scholarship Council(CSC).The opinions expressed herein reflect those of the authors only.The authors would like to acknowledge the following people for their assistance:WAN Xianrong and YI Jianxin,both with the Electronic In-formation School,Wuhan University.

10.16356/j.1005-1120.2024.05.010

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