Swarm Division-Based Aircraft Velocity Obstacle Optimization Considering Low-Carbon Emissions

Qingwei Zhong, Yingxue Yu (), Yongxiang Zhang, Jingwei Guo and Zian He
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Qingwei Zhong: College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China
Yingxue Yu: College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China
Yongxiang Zhang: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Jingwei Guo: Faculty of Business, City University of Macau, Macau SAR 999078, China
Zian He: Guangxi Air Traffic Management Sub-Bureau, Nanning 530031, China

Sustainability, 2024, vol. 16, issue 5, 1-27

Abstract: In the pursuit of sustainable aviation, this paper presents an innovative approach that adopts a swarm division strategy to enhance and refine the velocity obstacle (VO) method, guided by a low-carbon principle. A dynamic elliptical protection zone model forms the core of this innovative approach. Specifically, this dynamic elliptical protection zone is created based on the difference in aircraft velocity, and a swarm division strategy is introduced in this process. Initially, aircraft that share the same route and type, and have similar velocities and distances, are grouped into swarms. Then, the characteristics of the swarms, such as mass points, velocities, and protection zones, are recorded. Second, the collision cone (CC) between swarms is established, and planar geometrical analysis is used to determine the optimal relief velocity and heading of aircraft on the low-carbon objective while ensuring a safe interval between aircraft in the swarm during the relief period. Additionally, a swarm control algorithm is utilized to adjust the velocity of the aircraft by a small margin. Finally, simulation experiments are conducted using Python, revealing that the swarm relief efficiency of the enhanced VO method sees a notable increase of over 33%. Concurrently, the need for adjustments decreases by an average of 32.78%, while fuel savings reach as high as 70.18%. The strategy is real-time and operational, significantly reduces the air traffic controller (ATC) workload, improves flight efficiency and safety, and contributes positively to the reduction in carbon emissions, which is beneficial for the environment.

Keywords: low carbon; swarm control strategy; dynamic elliptical protection zone; velocity obstacle method optimization; geometric optimization algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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