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Aircraft swarm improved velocity obstacle methods considering low carbon and deviation
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Qingwei Zhong1, 2, Yingxue Yu1, 3, Su Liu**, 1, Rui Wang1, Jingwei Guo4, Weijun Pan2
China Safety Science Journal | 2026, 36(4) : 142 - 151
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China Safety Science Journal | 2026, 36(4): 142-151
Safety Technology and Engineering
Aircraft swarm improved velocity obstacle methods considering low carbon and deviation
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Qingwei Zhong1, 2, Yingxue Yu1, 3, Su Liu**, 1, Rui Wang1, Jingwei Guo4, Weijun Pan2
Affiliations
  • 1School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan Sichuan 618307, China
  • 2Key Laboratory of Flight Techniques and Flight Safety, Civil Aviation Flight University of China, Guanghan Sichuan, 618307, China
  • 3School of Electromechanical Engineering, Guangzhou City Construction College, Guangzhou Guangdong 510925, China
  • 4Faculty of Business, City University of Macau, Macau 999078, China
Published: 2026-04-28 doi: 10.16265/j.cnki.issn1003-3033.2026.04.0144
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In order to address the requirements of low-carbon operation and safety in aircraft conflict resolution, an IVO method based on adaptive elliptical protected zones was proposed, taking into account aircraft carbon emissions and speed adjustment deviations. First, adaptive elliptical protected zones were constructed according to the velocity differences among aircraft. Second, aircraft flying on the same route with similar velocity vectors and close spatial proximity were grouped into clusters, and key characteristics such as cluster centroids, velocity vectors, and safety regions were defined. Then, a cluster control algorithm was applied to reasonably adjust the velocity vectors of aircraft within each cluster, ensuring the maintenance of safe separation during conflict resolution. Subsequently, velocity obstacle cones were established between clusters. By incorporating constraints on the maximum allowable adjustment per unit time and combining planar geometric analysis with a mathematical optimization model, conflict-free velocities and headings with minimal deviation were determined under low-carbon objectives. Finally, dynamic behaviour analysis was conducted through numerical simulations implemented in Python. The results show that, compared with the traditional velocity obstacle method, the proposed approach improves conflict resolution efficiency by 87.5%, reduces the average adjustment magnitude by 86.67%, and achieves fuel savings of up to 37.36%, demonstrating its effectiveness for aircraft conflict resolution and operational optimization in complex air traffic environments.

low carbon  /  velocity adjustment deviation  /  aircraft swarm  /  improved velocity obstacle(IVO) method  /  aircraft conflict resolution
Qingwei Zhong, Yingxue Yu, Su Liu, Rui Wang, Jingwei Guo, Weijun Pan. Aircraft swarm improved velocity obstacle methods considering low carbon and deviation[J]. China Safety Science Journal, 2026 , 36 (4) : 142 -151 . DOI: 10.16265/j.cnki.issn1003-3033.2026.04.0144
Year 2026 volume 36 Issue 4
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2026.04.0144
  • Receive Date:2025-11-02
  • Online Date:2026-07-08
  • Published:2026-04-28
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  • Received:2025-11-02
  • Revised:2026-01-10
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Affiliations
    1School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan Sichuan 618307, China
    2Key Laboratory of Flight Techniques and Flight Safety, Civil Aviation Flight University of China, Guanghan Sichuan, 618307, China
    3School of Electromechanical Engineering, Guangzhou City Construction College, Guangzhou Guangdong 510925, China
    4Faculty of Business, City University of Macau, Macau 999078, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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