A hybrid distributed-centralized conflict resolution approach for multi-aircraft based on cooperative co-evolutionary

Conflict resolution （CR） plays a crucial role in safe air traffic management （ATM）. In this paper, we propose a new hybrid distributed-centralized tactical CR approach based on cooperative co-evolutionary named the CCDG （cooperative co-evolutionary with dynamic grouping） strategy to overcome the dra...

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Bibliographic Details
Published in:Science China. Information sciences 2013-12, Vol.56 (12), p.277-292
Main Authors: Zhang, XueJun, Guan, XiangMin, Hwang, Inseok, Cai, KaiQuan
Format: Article
Language:English
Subjects:
Air traffic management
Aircraft
China
Computer Science
Conflict resolution
Dynamics
Evolutionary
Evolutionary algorithms
Genetic algorithms
Information Systems and Communication Service
Optimization
Research Paper
Strategy
冲突解决
协同进化算法
合作
基础
最优路径
混合分布
空中交通管理
飞机
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Summary:Conflict resolution （CR） plays a crucial role in safe air traffic management （ATM）. In this paper, we propose a new hybrid distributed-centralized tactical CR approach based on cooperative co-evolutionary named the CCDG （cooperative co-evolutionary with dynamic grouping） strategy to overcome the drawbacks of the current two types of approaches, the totally centralized approach and distributed approach. Firstly, aircraft are divided into several sub-groups based on their interdependence. Besides, a dynamic grouping strategy is proposed to group the aircraft to better deal with the tight coupling among them. The sub-groups are adjusted dynamically as new conflicts appear after each iteration. Secondly, a fast genetic algorithm （GA） is used by each sub-group to optimize the paths of the aircraft simultaneously. Thirdly, the aircraft＇s optimal paths are obtained through cooperation among different sub-groups based on cooperative co-evolutionary （CC）. An experimental study on two illustrative scenarios is conducted to compare the CCDG method with some other existing approaches and it is shown that CCDG which can get the optimal solution effectively and efficiently in near real time, outperforms most of the existing approaches including Stratway, the fast GA, a general evolutionary path planner, as well as three well-known cooperative co-evolution algorithms.
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-013-4836-3