Abstract：The study of congestion evolution mechanism in terminal airspace is a vital measure to ensure the normal operation of terminal airspace. This paper divides congestion into two categories: its own structural causes and external causes, and establishes a corresponding analytical model for congestion formation and dissipation. Based on the characteristic indexes of traffic flow evolution and Greenshields theory, the cusp catastrophe analysis model for congestion mechanism is established. In order to verify the validity of the model, this study takes the Chengdu terminal airspace as the object and uses AirTOp software to generate simulation operation data. The results show that the designed model can effectively describe the macroscopic process of congestion evolution, and the mechanism of congestion evolution can be effectively analyzed through the changes of equivalent flow, density and wave speed in the segment.
[1] 中华人民共和国交通运输部.民用航空空中交通管理规则:CCAR-93TM-R6-2023[S/OL]. [2023-05-02]. https://www.gov.cn/zhengce/2022-11/03/content 5717885.htm. MINISTRY OF TRANSPORT OF THE PEOPLE′S REPUBLIC OF CHINA. Airtraffic management rules for civil aviation:CCAR-93TM-R6-2023[S/OL]. [2023-05-02]. https://www.gov.cn/zhengce/2022-11/03/content 5717885.htm. [2] 高旗, 初建宇, 李印凤. 基于PSO-BP神经网络的终端区拥堵等级预测模型[J]. 航空计算技术, 2019, 49(6): 57-61. GAO Q, CHU J Y, LI Y F. Prediction model of congestion level in terminal area based on PSO-BP neural network[J]. Aeronautical Computing Technique, 2019, 49(6): 57-61. [3] ATTWOOLL V W. Thecosts of terminal area delays[J]. Journal of Navigation, 1968, 21(1): 66-80. [4] 蒋京芩. 终端区空中交通拥堵态势演变机理研究[D]. 南京: 南京航空航天大学, 2017. JIANG J Q. Research onevolution mechanism of air traffic congestion in terminal area[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017. [5] LAVANDIER J, ISLAMI A, DELAHAYE D,et al. Selective simulated annealing for large scale airspace congestion mitigation[J]. Aerospace, 2021, 8(10): 1-16. [6] REN J, QU S, WANG L, et al. Anen route capacity optimization model based on air traffic control process[J]. Mathematical Biosciences and Engineering, 2022, 19(4): 4277-4299. [7] YE B, SHERRY L, CHEN C H, et al. Comparison ofalternative route selection strategies based on simulation optimization[J]. Chinese Journal of Aeronautics, 2016, 29(6): 1749-1761. [8] XU Y, ZHANG H, LIAO Z, et al. A dynamic air traffic model for analyzing relationship patterns of traffic flow parameters in terminal airspace[J]. Aerospace Science and Technology, 2016, 55(8): 10-23. [9] 谭娟, 王胜春. 基于深度学习的交通拥堵预测模型研究[J]. 计算机应用研究, 2015, 32(10): 2951-2954. TAN J, WANG S C. Research on preditiction model for traffic congestion based on deep learning[J]. Application Research of Computers, 2015, 32(10): 2951-2954. [10] 胡启洲, 孙煦. 基于多维联系数的城市路网交通拥堵态势监控模型[J]. 中国公路学报, 2013, 26(6): 143-149. HU Q Z, SUN X. Model for traffic congestion state monitor in urban road network based on multi-dimension connection number[J]. China Journal of Highway and Transport, 2013, 26(6): 143-149. [11] 王英平, 王殿海, 杨少辉, 等. 突变理论在交通流分析理论中应用综述[J]. 交通运输系统工程与信息, 2005, 5(6): 68-71. WANG Y P, WANG D H, YANG S H, et al. A comprehensive review over the application of catastrophe theory in traffic flow[J]. Journal of Transportation Systems Engineering and Information Technology, 2005, 5(6): 68-71. [12] 王祥雪. 城市快速路交通拥堵机理及状态判别理论与方法研究[D]. 广州: 华南理工大学, 2018. WANG X X. Research on thetheories and techniques of urban expressway traffic congestion evolution mechanism and condition recognition[D]. Guangzhou: South China University of Technology 2018. [13] 黄艳国. 城市道路交通拥堵机理及控制方法研究[D]. 广州: 华南理工大学, 2015. HUANG Y G. Research ontraffic congestion mechanism and traffic control method for urban road[D]. Guangzhou: South China University of Technology, 2015. [14] 许伦辉, 王祥雪. 基于尖点突变的城市快速路交通流拥堵时空演化研究[J]. 公路, 2016, 61(12): 133-144. XU L H, WANG X X. Research ontraffic flow congestion space-time evolution of urban expressway based on cusp catastrophe theory[J]. Highway, 2016, 61(12): 133-144. [15] 张洪海, 杨磊, 别翌荟, 等. 终端区进场交通流广义跟驰行为与复杂相变分析[J]. 航空学报, 2015, 36(3): 251-263. ZHANG H H, YANG L, BIE Y H, et al. Analysis on generalized following behavior and complex phase-transition law of approaching traffic flow in terminal airspace[J]. Acta Aeronautica Astronautica Sinica, 2015, 36(3): 251-263. [16] 杨磊. 终端区交通流复杂动态特性与拥堵控制方法[D]. 南京: 南京航空航天大学, 2018. YANG L. Studies oncomplex dynamics and congestion mitigation methods of air traffic flow in terminal airspace[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2018. [17] ABDELAZIZ K K,NICAISE Y, SÉGUIS L, et al. Influence of land use land cover change on groundwater recharge in the continental terminal area of abidjan, ivory coast[J]. Journal of Water Resource and Protection, 2020, 12(5): 431-453. [18] 何兆成, 周亚强, 余志. 基于数据可视化的区域交通状态特征评价方法[J]. 交通运输工程学报, 2016, 16(1): 133-140. HE Z C, ZHOU Y Q, YU Z. Regionaltraffic state evaluation method based on data visualization[J]. Journal of Traffic and Transportation Engineering, 2016, 16(1): 133-140. [19] 许学吉, 孙樊荣, 沐瑶, 等. 基于雷达轨迹数据的航段拥堵分析[J]. 武汉理工大学学报(交通科学与工程版), 2022, 46(4): 624-628. XU X J, SUN F R, MU Y,et al. Research on segment congestion based on radar trajectory data[J]. Journal of Wuhan University of Technology(Transportation Science & Engineering), 2022, 46(4): 624-628. [20] OLIVE X, MORIO J. Trajectory clustering of air traffic flows around airports[J]. Aerospace Science and Technology, 2019, 84(1): 776-781. [21] GERBEND J, ROGIER L. Disruption in the air: the impact of flight rerouting due to air traffic control strikes[J]. Transportation Research Part D: Transport and Environment, 2021, 90(1): 1-17. [22] 刘浩敏, 曲大义, 宋慧, 等. 快速路交通流状态突变边界提取及其演化规律[DB/OL]. [2023-04-20]. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C45S0n9fL2suRadTyEVl2pW9UrhTDCdPD65FzzQr8IgOxBG9iAGtsSkSIWCOQqaoQU4i4RYrzsdmk0KMAMaFoy3Z&uniplatform=NZKPT. LIU H M, QU D Y, SONG H,et al. Extraction of catastrophe boundary and evolution of expressway traffic flow state[DB/OL]. [2023-04-20]. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C45S0n9fL2suRadTyEVl2pW9UrhTDCdPD65FzzQr8IgOxBG9iAGtsSkSIW COQqaoQU4i4RYrzsdmk0KMAMaFoy3Z&uniplatform=NZKPT. [23] HUANG Y G, ZHANG H M, LIU H J, et al. An analysis of the catastrophe model and catastrophe characteristics of traffic flow based on cusp catastrophe theory[J]. Journal of Advanced Transportation, 2022(1): 1-11.
