| Citation: | AI Yi, WAN Qifeng, HAN Xun, LI Yueyang, YU Yingxue, CONG Wei. A Risk Assessment Method of Multi-aircraft Interaction for Complex Airspace[J]. Journal of Transport Information and Safety, 2024, 42(3): 1-10. doi: 10.3963/j.jssn.1674-4861.2024.03.001
|
| [1] |
中国民用航空局. 2017年全国民航航班运行效率报告[R]. 北京: 中国民用航空局运行监控中心, 2018.
Civil Aviation Administration of China(CAAC). Report on national civil aviation flight operation efficiency in 2017[R]. Beijing: Center for CAAC Operation Monitoring, 2018. (in Chinese)
|
| [2] |
VISINTINI A, GLOVER W, LYGEROS J, et al, Monte Carlo optimization for conflict resolution in air traffic control[J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(4)470-482. doi: 10.1109/TITS.2006.883108
|
| [3] |
WANG J, WU J, LI Y. The driving safety field based on driv-er-vehicle-road interactions[J]. IEEE Transactions on Intelli-gent Transportation Systems, 2015, 16(4): 2203-2214. doi: 10.1109/TITS.2015.2401837
|
| [4] |
朱永文, 谢华, 蒲钒, 等. 空域网格化方法及其在空管中的应用研究[J]. 航空工程进展, 2021, 12(4): 12-24.
ZHU Y W, XIE H, PU F, et al. Spatial grid method and its application in air traffic control[J]. Advances in Aeronauti-cal Science and Engineering, 2021, 12(4): 12-24. (in Chinese)
|
| [5] |
王红勇, 温瑞英. 基于复杂网络的空中交通态势风险评估方法[J]. 中国安全科学学报, 2018, 28(5): 172-178.
WANG H Y, WEN R Y. Complex network-based risk assess-ment method for air traffic posture[J] China Safety Science Journal, 2018, 28(5): 172-178. (in Chinese)
|
| [6] |
LI B, DU W, ZHANG Y, et al. A deep unsupervised learning approach for airspace complexity evaluation[J]. IEEE Trans-actions on Intelligent Transportation Systems, 2022, 23(8): 11739-11751. doi: 10.1109/TITS.2021.3106779
|
| [7] |
JIANG Y, WANG S, YAO Z, et al. A cellular automata model for mixed traffic flow considering the driving behavior of con-nected automated vehicle platoons[J]. Physica A, 2021, 582: 126262. doi: 10.1016/j.physa.2021.126262
|
| [8] |
LI L, WANG C, ZHANG Y. Microscopic state evolution mod-el of mixed traffic flow based on potential field theory[J]. Physica A, 2022, 607: 128185. doi: 10.1016/j.physa.2022.128185
|
| [9] |
BYRNE S, NAEEM W, FERGUSON S. Improved APF strate-gies for dual-arm local motion planning[J]. Transaction of the Institute of Measurement and Control, 2015, 37(1): 73-90. doi: 10.1177/0142331214532002
|
| [10] |
WOLF M T, BURDICK J W. Artificial potential functions for highway driving with collision avoidance. [C]. IEEE In-ternational Conference on Robotics Automation, Pasadena: IEEE, 2008.
|
| [11] |
陈永, 贺红, 张薇, 等. 基于场力的驾驶员影响因素交通流动力学模型[J]. 力学学报, 2018, 50(5): 1219-1234.
CHEN Y, HE H, ZHANG W, et al. A driver influenced fac-tor traffic flow dynamics model based on field forces[J]. Chi-nese Journal of Theoretical and Applied Mechanics, 2018, 50(5): 1219-1234. (in Chinese)
|
| [12] |
NI D, WANG H. A unified perspective on traffic flow theory Part Ⅲ: validation and benchmarking. [J]. Applied Mathe-matical Sciences, 2013, 7(40): 1965-1982.
|
| [13] |
WANG J, WU J, ZHENG X, et al. Driving safety field theo-ry modeling and its application in precollision warning sys-tem[J]. Transportation Research Part C: Emerging Technolo-gies, 2016, 72: 306-324. doi: 10.1016/j.trc.2016.10.003
|
| [14] |
管祥民, 吕人力. 基于混合人工势场与蚁群算法的多飞行器冲突解脱方法[J]. 武汉理工大学学报(交通科学与工程版), 2020, 44(1): 28-33. doi: 10.3963/j.issn.2095-3844.2020.01.006
GUAN X M, LYU R L. Conflict resolution method for multi-ple aircraft based on hybrid artificial potential field and ant colony algorithm[J]. Journal of Wuhan University of Tech-nology(Transportation Science & Engineering), 2020, 44(1): 28-33(in Chinese). doi: 10.3963/j.issn.2095-3844.2020.01.006
|
| [15] |
LIU W, LI Z. Comprehensive predictive control method for automated vehicles in dynamic traffic circumstances[J]. IET Intelligent Transport Systems, 2018, 12(10): 1455-1463. doi: 10.1049/iet-its.2018.5142
|
| [16] |
LI M, SONG X, CAO H, et al. Shared control with a novel dynamic authority allocation strategy based on game theory and driving safety field[J]. Mechanical Systems and Signal Processing, 2019, 124: 199-216. doi: 10.1016/j.ymssp.2019.01.040
|
| [17] |
庞笔照. 航路网络关键结构分析及优化[D]. 天津: 中国民航大学, 2019.
PANG B Z. Critical structure analysis and optimization for air route network[D]. Tianjing: Civil Aviation University of China, 2019. (in Chinese)
|
| [18] |
张旭. 繁忙空域的临时航线划设与评估研究[D]. 天津: 中国民航大学, 2021.
ZHANG X. Study on temporary route planning and evalua-tion in busy airspace[D]. Tianjing: Civil Aviation University of China, 2021. (in Chines)
|
| [19] |
LI L H, GAN J, QU X, et al. A novel lane-changing model of connected and automated vehicles: using the safety potential field theory[J]. Physica A, 2020, 559: 125039. doi: 10.1016/j.physa.2020.125039
|
| [20] |
LI L H, GAN J, QU X, et al. Dynamic driving risk potential field model under the connected and automated vehicles en-vironment and its application in car-following modeling[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(1): 122-141. doi: 10.1109/TITS.2020.3008284
|
| [21] |
徐涛, 陈雪蕊, 吕宗平. 基于航迹聚类的终端区飞行程序轨迹表示[J]. 四川大学学报(工程科学版), 2016, 48(6): 188-196.
XU T, CHEN X R, LYU Z P. Flight procedure representation of terminal area based on flight tracks clustering[J]. Advanced Engineering Sciences, 2016, 48(6): 188-196. (in Chinese)
|
| [22] |
AI Y, LI Y Y, HAN X, et al. Real-time risk assessment meth-od for multi-aircraft interaction based on potential field theo-ry[J]. Physica A: Statistical Mechanics and its Applications, 2024, 633: 129423. doi: 10.1016/j.physa.2023.129423
|
| [23] |
冯霞, 孙琦琦, 左海超. 基于Informer的客机长时4D航迹预测方法[J]. 交通信息与安全, 2023, 41(4): 111-121.
FENG X, SUN Q Q, ZUO H C. A method for predicting long-term 4D trajectory of airplanes based on informer[J]. Journal of Transport Information and Safety, 2023, 41(04): 111-121. (in Chinese)
|
| [24] |
纪新雨, 初建宇, 李印凤, 等. 基于改进CURE算法的终端区航迹聚类[J]. 指挥信息系统与技术, 2021, 12(6): 63-67.
JI X Y, CHU J Y, LI Y F, et al. Terminal area trajectory cluster-ing based on improved cure algorithm[J]. Command Informa-tion System and Technology, 2021, 12(6): 63-67. (in Chinese)
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