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Volume 45 Issue 4
Apr.  2023
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Article Contents
WANG Yan-tao, LIU Kun, ZHAO Yi-fei. Flight alternate optimization scheme in dangerous weather based on multiexpectation[J]. Chinese Journal of Engineering, 2023, 45(4): 654-662. doi: 10.13374/j.issn2095-9389.2021.12.30.002
Citation: WANG Yan-tao, LIU Kun, ZHAO Yi-fei. Flight alternate optimization scheme in dangerous weather based on multiexpectation[J]. Chinese Journal of Engineering, 2023, 45(4): 654-662. doi: 10.13374/j.issn2095-9389.2021.12.30.002

Flight alternate optimization scheme in dangerous weather based on multiexpectation

doi: 10.13374/j.issn2095-9389.2021.12.30.002
More Information
  • Corresponding author: E-mail: caucwyt@126.com
  • Received Date: 2021-12-30
    Available Online: 2022-04-02
  • Publish Date: 2023-04-01
  • Aircraft landing with low fuel is usually caused by diversion decision changes in the air. It could lead to an unsafe event. To solve the problem of collective alternate landings of multiple flights in the area, the most complex situation is selected, that is, when the weather in the route or terminal area is dangerous. However, in this situation, when the pilot announces diversion, many are unacceptable by the airport due to limited aircraft stand. Therefore, this study establishes a decision-making approach to help air traffic controllers and airlines choose suitable alternate airports since accurate fly limit zone conditions can keep the aircraft out of dangerous weather and a short diversion route can avoid the low fuel situation, both of which can increase the safety of the diversion process. The basic conditions of the fly limit zone under dangerous weather are obtained by combining meteorological data and historic tracks. Here, A* and the improved gray wolf Dijkstra algorithm are used to plan the diversion path for two different routes to the alternate aerodrome: maneuvering flight and flying along the route. First, considering the shortest total flight time of alternate flight as the single objective and subsequently integrating the expectations of flight, control, airport, and airline, a multi-objective function is constructed, the dynamic decision-making time interval is defined, and a dynamic optimization scheme of multi-flight alternate in the region based on a single objective and multi-objective is proposed. The single-objective scheme focuses on the safe aspect of diversion, while the multi-objective scheme focuses on preventing airport rejection. The multi-objective scheme can enable the flight to land quickly, ensure safety, and consider the expectations of multiple parties to avoid diverting simultaneously. Using the “8.12” North China large area alternate landing data, the total flight time obtained by selecting the direct flight A* algorithm is reduced by 100 and 62 min, respectively, and the total flight time obtained by the improved gray wolf Dijkstra algorithm based on the route is reduced by 73 and 14 min. Moreover, in the multi-objective scheme, the overall time of flight resumption to the original destination is 63 min earlier, and the total cost is reduced by 62900 yuan. Although multiple diversion still occurs on CA991, the process is within the safety range. Therefore, results indicate that the scheme considers the needs of multiple parties and improves the economy to ensure the safety of flight alternate landing.

     

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  • [1]
    Zhang Y, Hansen M. Real-time intermodal substitution: Strategy for airline recovery from schedule perturbation and for mitigation of airport congestion. Transportation Res Record, 2008, 2052(1): 90 doi: 10.3141/2052-11
    [2]
    Mukherjee A, Hansen M. A dynamic rerouting model for air traffic flow management. Transp Res B Methodol, 2009, 43(1): 159 doi: 10.1016/j.trb.2008.05.011
    [3]
    Yoon Y, Hansen M, Ball M O. Optimal route decision with a geometric ground-airborne hybrid model under weather uncertainty. Transp Res E Logist Transp Rev, 2012, 48(1): 34 doi: 10.1016/j.tre.2011.05.005
    [4]
    di Ciccio C, van der Aa H, Cabanillas C, et al. Detecting flight trajectory anomalies and predicting diversions in freight transportation. Decis Support Syst, 2016, 88: 1 doi: 10.1016/j.dss.2016.05.004
    [5]
    Ryerson M S. Diversion ahead: Modeling the factors driving diversion airport choice. J Infrastruct Syst, 2018, 24(1): 04017039 doi: 10.1061/(ASCE)IS.1943-555X.0000407
    [6]
    Malandri C, Mantecchini L, Paganelli F, et al. Impacts of unplanned aircraft diversions on airport ground operations. Transp Res Procedia, 2020, 47: 537 doi: 10.1016/j.trpro.2020.03.129
    [7]
    ?pák M, Olexa P. Enhancement of the diversion airport selection methodology. Transp Res Procedia, 2020, 51: 232 doi: 10.1016/j.trpro.2020.11.026
    [8]
    李雄, 徐肖豪, 趙嶷飛, 等. 散點狀分布危險天氣區域下的航班改航路徑規劃. 航空學報, 2009, 30(12):2342 doi: 10.3321/j.issn:1000-6893.2009.12.016

    Li X, Xu X H, Zhao Y F, et al. Flight rerouting path planning in dispersedly distributed severe weather areas. Acta Aeronaut Astronaut Sin, 2009, 30(12): 2342 doi: 10.3321/j.issn:1000-6893.2009.12.016
    [9]
    王飛, 王紅勇. 基于Maklink圖和遺傳算法的改航路徑規劃方法研究. 交通運輸系統工程與信息, 2014, 14(5):154 doi: 10.3969/j.issn.1009-6744.2014.05.023

    Wang F, Wang H Y. A re-routing path planning method based on maklink graph and GA algorithm. J Transp Syst Eng Inf Technol, 2014, 14(5): 154 doi: 10.3969/j.issn.1009-6744.2014.05.023
    [10]
    陳正茂, 林毅, 楊波. 基于歷史數據的空中改航算法研究. 工程科學與技術, 2018, 50(4):110

    Chen Z M, Lin Y, Yang B. Study on algorithm for rerouting based on historical data. Adv Eng Sci, 2018, 50(4): 110
    [11]
    陳可嘉, 陳琳琳. 危險天氣下航班等待與改航的實時集成優化. 南京航空航天大學學報, 2019, 51(6):763 doi: 10.16356/j.1005-2615.2019.06.005

    Chen K J, Chen L L. Aircraft holding and rerouting real-time integrated optimization under adverse weather. J Nanjing Univ Aeronaut Astronaut, 2019, 51(6): 763 doi: 10.16356/j.1005-2615.2019.06.005
    [12]
    陳雨童, 胡明華, 楊磊, 等. 受限航路空域自主航跡規劃與沖突管理技術. 航空學報, 2020, 41(9):324045

    Chen Y T, Hu M H, Yang L, et al. Autonomous trajectory planning and conflict management technology in restricted airspace. Acta Aeronaut Astronaut Sin, 2020, 41(9): 324045
    [13]
    臧寧寧, 池宏, 邵雪焱, 等. 返航備降航班高風險頻發子集搜索模型. 運籌與管理, 2012, 21(3):105 doi: 10.3969/j.issn.1007-3221.2012.03.017

    Zang N N, Chi H, Shao X Y, et al. The search model on the high frequent risk subsets of the diversion or turning back flights. Oper Res Manag Sci, 2012, 21(3): 105 doi: 10.3969/j.issn.1007-3221.2012.03.017
    [14]
    趙嶷飛, 石艷麗, 王紅勇. 基于線性規劃的航班備降優化模型研究. 科學技術與工程, 2013, 13(27):8222 doi: 10.3969/j.issn.1671-1815.2013.27.057

    Zhao Y F, Shi Y L, Wang H Y. Research on the optimization model of flights alternate based on linear programming. Sci Technol Eng, 2013, 13(27): 8222 doi: 10.3969/j.issn.1671-1815.2013.27.057
    [15]
    王巖韜, 唐建勛, 趙嶷飛. 基于機位可調整的航班空中備降優化. 安全與環境學報, 2018, 18(2):636 doi: 10.13637/j.issn.1009-6094.2018.02.041

    Wang Y T, Tang J X, Zhao Y F. On the flight alternate optimization based on the adjustable apron. J Saf Environ, 2018, 18(2): 636 doi: 10.13637/j.issn.1009-6094.2018.02.041
    [16]
    劉蘋妮, 甘旭升, 唐雪琴, 等. 基于改進WOA的軍用機場失效下的備降場選擇策略. 火力與指揮控制, 2021, 46(9):88 doi: 10.3969/j.issn.1002-0640.2021.09.016

    Liu P N, Gan X S, Tang X Q, et al. Research on repair problem of aviation network under airport failure based on modified WOA. Fire Control Command Control, 2021, 46(9): 88 doi: 10.3969/j.issn.1002-0640.2021.09.016
    [17]
    Krozel J, Lee C, Mitchell J S B. Turn-constrained route planning for avoiding hazardous weather. Air Traffic Control Q, 2006, 14(2): 159 doi: 10.2514/atcq.14.2.159
    [18]
    DeLaura R, Evans J. An exploratory study of modeling enroute pilot convective storm flight deviation behavior // 12th Conference on Aviation Range and Aerospace Meteorology. Lexington, 2006: 1
    [19]
    何光勤, 魯力, 胡敬玉, 等. 基于最小二乘法的雷暴天氣下飛行改航決策研究. 安全與環境工程, 2019, 26(4):171 doi: 10.13578/j.cnki.issn.1671-1556.2019.04.027

    He G Q, Lu L, Hu J Y, et al. Flight track change decision in thunderstorm based on least square method. Saf Environ Eng, 2019, 26(4): 171 doi: 10.13578/j.cnki.issn.1671-1556.2019.04.027
    [20]
    尹麗云, 梅寒, 張騰飛, 等. 云南中部一次出現多個超級單體雹暴的強對流過程環境場和雷達回波特征. 氣象, 2021, 47(4):424 doi: 10.7519/j.issn.1000-0526.2021.04.004

    Yin L Y, Mei H, Zhang T F, et al. Environmental conditions and radar characteristics of a severe convective hailstorm with multiple supercells in central Yunnan Province. Meteorological Monthly, 2021, 47(4): 424 doi: 10.7519/j.issn.1000-0526.2021.04.004
    [21]
    Precup R E, David R C, Petriu E M. Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity. IEEE Trans Ind Electron, 2017, 64(1): 527 doi: 10.1109/TIE.2016.2607698
    [22]
    劉二輝, 姚錫凡, 劉敏, 等. 基于改進灰狼優化算法的自動導引小車路徑規劃及其實現原型平臺. 計算機集成制造系統, 2018, 24(11):2779 doi: 10.13196/j.cims.2018.11.013

    Liu E H, Yao X F, Liu M, et al. AGV path planning based on improved grey wolf optimization algorithm and its implementation prototype platform. Comput Integr Manuf Syst, 2018, 24(11): 2779 doi: 10.13196/j.cims.2018.11.013
    [23]
    田文, 楊帆, 尹嘉男, 等. 航路時空資源分配的多目標優化方法. 交通運輸工程學報, 2020, 20(6):218 doi: 10.19818/j.cnki.1671-1637.2020.06.019

    Tian W, Yang F, Yin J N, et al. Multi-objective optimization method of air route space-time resources allocation. J Traffic Transp Eng, 2020, 20(6): 218 doi: 10.19818/j.cnki.1671-1637.2020.06.019
    [24]
    徐敏, 黃沛霖, 燕瑛, 等. 基于動態指標的飛機方案多目標優化方法. 北京航空航天大學學報, 2014, 40(7):965 doi: 10.13700/j.bh.1001-5965.2013.0447

    Xu M, Huang P L, Yan Y, et al. Dynamic index based method for multi-objective optimization in aircraft conceptual design. J Beijing Univ Aeronaut Astronaut, 2014, 40(7): 965 doi: 10.13700/j.bh.1001-5965.2013.0447
    [25]
    李航, 郭曉梅, 胡小兵. 災害性天氣下航空公司天氣成本測算模型. 中國安全科學學報, 2019, 29(6):7 doi: 10.16265/j.cnki.issn1003-3033.2019.06.002

    Li H, Guo X M, Hu X B. A calculation model for airlines’ weather-related costs under disastrous weather conditions. China Saf Sci J, 2019, 29(6): 7 doi: 10.16265/j.cnki.issn1003-3033.2019.06.002
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