基于速度障碍法的飞行冲突网络建模与分析

doi:10.12305/j.issn.1001-506X.2021.08.18

Abstract

Abstract:

Due to the lack of information such as the speed and direction of aircraft, the complex network model based on the relative position relationship has limited ability to reflect the conflicts between aircrafts and the complex situation of air traffic. In order to solve this problem, speed obstacle model is used in this paper to optimize the connection and weight between aircraft nodes in the aircraft state network. While considering the proximity of aircraft to positions, the direction and speed of aircraft are concerned, so that the network can reflect more intrinsic properties of airspace system. Program simulation and verification by radar data of Changshui Airport show that the model in this paper can more accurately reflect the airspace complexity information and the conflict between aircrafts compared with the aircraft state network, so that the number of false alarms for flight conflicts are reduced and the value of network information is improved.

Key words: velocity obstacle method, flight conflict, complex network, air traffic control, controller

CLC Number:

V355

Kexin BI, Minggong WU, Wenbin ZHANG, Xiangxi WEN, Kan DU. Modeling and analysis of flight conflict network based onvelocity obstacle method[J]. Systems Engineering and Electronics, 2021, 43(8): 2163-2173.

Figures/Tables 13

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References 21

1	International Civil Aviation Organization. Global air traffic management operational concept[R]. Montreal: International Civil Aviation Organization, 2005.
2	中国民用航空局. 中国民航空管基于航迹运行(TBO)运行概念[R]. 北京: 空中交通管理局, 2019.
	Civil Aviation Administration of China. The concept of trajectory based operation (TBO) in China civil aviation air traffic management[R]. Beijing: Air Traffic Management Bureau, 2019.
3	LAUDEMAN I V, SHELDEN S G, BRANSTROM R. Dynamic density: an air traffic management metric[R]. California: National Aeronautics and Space Administration, 1998.
4	DELAHAYE D, PUECHMOREL S. Air traffic complexity: towards intrinsic metrics[C]//Proc. of the 3rd USA Europe Air Traffic Management Research and Development Seminar, 2000.
5	DELAHAYE D , PUECHMOREL S , HANSMAN R J . Airtraffic complexity map based on non linear dynamicalsystems[J]. Air Traffic Control, 2004, 12 (4): 367- 388. doi: 10.2514/atcq.12.4.367
6	张进, 胡明华, 张晨. 空中交通管理中的复杂性研究[J]. 航空学报, 2009, 30 (11): 2132- 2142. doi: 10.3321/j.issn:1000-6893.2009.11.019
	ZHANG J , HU M H , ZHANG C . Complexity research in air traffic management[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30 (11): 2132- 2142. doi: 10.3321/j.issn:1000-6893.2009.11.019
7	XIAO M M , ZHANG J , CAI K Q . ATCEM: a synthetic model for evaluating air traffic complexity[J]. Journal of Advanced Transportation, 2016, 50 (3): 315- 325. doi: 10.1002/atr.1321
8	ZHU X , CAO X B , CAI K Q . Measuring air traffic complexity based on small samples[J]. Chinese Journal of Aeronautics, 2017, 30 (4): 1493- 1505. doi: 10.1016/j.cja.2017.04.018
9	CAO X B , ZHU X , TIAN Z C . A knowledge-transfer-based learning framework for airspace operation complexity evaluation[J]. Transportation Research Part C-Emerging Technologies, 2018, 95 (1): 61- 81.
10	ANDRASI P , RADISIC T , NOVAK D . Subjective air traffic complexity estimation using artificial neural networks[J]. Promet-Traffic & Transportation, 2019, 31 (4): 377- 386.
11	MALAKIS S , PSAROS P , KONTOGIANNIS T . Classification of air traffic control scenarios using decision trees: insights from a field study in terminal approach radar environment[J]. Cognition Technology & Work, 2020, 22 (1): 159- 179. doi: 10.1007/s10111-019-00562-7
12	王红勇, 赵嶷飞, 温瑞英. 基于复杂网络的空中交通复杂性度量方法[J]. 系统工程, 2014, 32 (3): 112- 118.
	WANG H Y , ZHAO Y F , WEN R Y . Air traffic complexity metrics based on complex networks[J]. Systems Engineering, 2014, 32 (3): 112- 118.
13	WANG H Y , WEN R Y , ZHAO Y F . Analysis of topological characteristic in air traffic situation networks[J]. Proceedings of the Institution of Mechanical Engineers Part G: Journal of Aerospace Engineering, 2015, 229 (13): 2497- 2505. doi: 10.1177/0954410015578482
14	WANG H Y , SONG Z Q , WEN R Y . Study on evolution characteristics of air traffic situation complexity based on complex network theory[J]. Aerospace Science and Technology, 2016, 58 (1): 518- 528.
15	WANG H Y , XU X H , ZHAO Y F . Empirical analysis of aircraft clusters in air traffic situation networks[J]. Proceedings of the Institution of Mechanical Engineers Part G: Journal of Aerospace Engineering, 2017, 231 (9): 1718- 1731. doi: 10.1177/0954410016660870
16	吴明功, 王泽坤, 甘旭升, 等. 基于复杂网络理论的关键飞行冲突点识别[J]. 西北工业大学学报, 2020, 38 (2): 279- 287. doi: 10.3969/j.issn.1000-2758.2020.02.007
	WU M G , WANG Z K , GAN X S , et al. Identification of key flight conflict nodes based on complex network theory[J]. Journal of Northwestern Polytechnical University, 2020, 38 (2): 279- 287. doi: 10.3969/j.issn.1000-2758.2020.02.007
17	吴明功, 叶泽龙, 温祥西, 等. 基于复杂网络的空中交通复杂性识别方法[J]. 北京航空航天大学学报, 2020, 46 (5): 839- 850.
	WU M G , YE Z L , WEN X X , et al. Air traffic complexity recognition based on complex networks[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46 (5): 839- 850.
18	JIANG X R , WEN X X , WU M G . A complex network analysis approach for identifying air traffic congestion based on independent component analysis[J]. Physica A-Statistical Mechanics and its Applications, 2019, 523 (1): 364- 381.
19	FIORINI P . Motion planning in dynamic environments using velocity obstacles[J]. International Journal of Robotics Research, 1998, 17 (7): 760- 772. doi: 10.1177/027836499801700706
20	DURAND N , BARNIER N . Does ATM need centralized coordination? Autonomous conflict resolution analysis in a constrained speed environment[J]. Air Traffic Control Quarterly, 2015, 23 (4): 710- 712.
21	王倩茹, 岳炼. 昆明机场低能见度特征分析[J]. 科技与创新, 2020, 5, 72- 74.
	WANG Q R , YUE L . Analysis of low visibility characteristics at kunming airport[J]. Science and Technology & Innovation, 2020, 5, 72- 74.

分布	架数	飞行状态网络			飞行冲突网络
分布	架数	C	D_l	NE	C	D_l	NE
均匀分布	10	0.297 1	0.134 2	0.170 9	0.046 5	0.050 1	0.057 0
	20	0.565 5	0.180 9	0.316 9	0.149 3	0.057 0	0.076 9
	30	0.646 5	0.220 2	0.448 5	0.243 6	0.065 1	0.106 1
	40	0.684 6	0.240 4	0.489 8	0.332 1	0.077 3	0.158 2
	50	0.696 8	0.250 3	0.493 3	0.392 2	0.092 8	0.234 1
正态分布	10	0.513 4	0.279 5	0.383 6	0.129 0	0.103 0	0.133 7
	20	0.655 8	0.331 4	0.484 5	0.299 1	0.143 7	0.248 7
	30	0.692 3	0.344 2	0.492 0	0.384 6	0.184 6	0.370 0
	40	0.712 3	0.353 0	0.493 7	0.427 1	0.216 9	0.454 1
	50	0.719 7	0.355 3	0.492 5	0.454 3	0.239 2	0.482 9

节点	时刻1	时刻2	时刻3	时刻4	时刻5	时刻6
1	(3, 11)	(5, 11)	(12, 11)	(19, 14)	(22, 17)	(23, 16)
2	(24, 35)	(24, 33)	(27, 28)	(23, 29)	(27, 23)	(24, 34)
3	(31, 52)	(32, 50)	(27, 44)	(24, 38)	(26, 38)	(26, 39)
4	(32, 22)	(32, 22)	(29, 29)	(31, 30)	(33, 34)	(32, 20)
5	(36, 13)	(35, 11)	(34, 11)	(32, 7)	(37, 7)	(27, 1)
6	(37, 30)	(36, 29)	(40, 27)	(33, 28)	(36, 27)	(33, 21)
7	(38, 29)	(39, 29)	(37, 30)	(47, 29)	(48, 33)	(49, 30)
⋯	⋯	⋯	⋯	⋯	⋯	⋯

时刻	飞行状态网络			飞行冲突网络
时刻	C	D_l	NE	C	D_l	NE
1	0.771 8	0.442 3	0.541 2	0.557 5	0.338 0	0.629 8
2	0.733 1	0.407 6	0.522 1	0.459 9	0.290 2	0.458 1
3	0.749 6	0.360 9	0.498 4	0.463 2	0.240 3	0.451 2
4	0.763 7	0.425 5	0.568 1	0.406 6	0.271 8	0.492 0
5	0.778 9	0.398 4	0.551 3	0.496 5	0.303 3	0.630 8
6	0.799 6	0.415 9	0.552 7	0.597 6	0.280 2	0.624 7

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Modeling and analysis of flight conflict network based onvelocity obstacle method

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