A strategic conflict avoidance approach based on cooperative coevolutionary with the dynamic grouping strategy

Abstract

Conflict avoidance plays a crucial role in guaranteeing the safety and efficiency of the air traffic management system. Recently, the strategic conflict avoidance (SCA) problem has attracted more and more attention. Taking into consideration the large-scale flight planning in a global view, SCA can be formulated as a large-scale combinatorial optimisation problem with complex constraints and tight couplings between variables, which is difficult to solve. In this paper, an SCA approach based on the cooperative coevolution algorithm combined with a new decomposition strategy is proposed to prevent the premature convergence and improve the search capability. The flights are divided into several groups using the new grouping strategy, referred to as the dynamic grouping strategy, which takes full advantage of the prior knowledge of the problem to better deal with the tight couplings among flights through maximising the chance of putting flights with conflicts in the same group, compared with existing grouping strategies. Then, a tuned genetic algorithm (GA) is applied to different groups simultaneously to resolve conflicts. Finally, the high-quality solutions are obtained through cooperation between different groups based on cooperative coevolution. Simulation results using real flight data from the China air route network and daily flight plans demonstrate that the proposed algorithm can reduce the number of conflicts and the average delay effectively, outperforming existing approaches including GAs, the memetic algorithm, and the cooperative coevolution algorithms with different well-known grouping strategies.

Keywords:

• conflict avoidance
• large-scale flight planning
• dynamic grouping strategy
• cooperative coevolution

Additional information

Funding

This work was supported by the National High Technology Research and Development Program of China [grant number 2011AA110101]; the National Basic Research Program of China [grant number 2011CB707000]; the Foundation for Innovative Research Groups of the National Natural Science Foundation of China [grant number 61221061]; China Scholarship Council.

Notes on contributors

Xiangmin Guan

Xiangmin Guan is a PhD student in the School of Electronic and Information Engineering at Beihang University. He received his BS degree from Hubei University in 2007. He was a visiting student of the School of Aeronautics and Astronautics at Purdue University in the USA from September 2012 to September 2013. His area of research includes air traffic control, intelligence computation, air traffic flow management, and optimisation.

Xuejun Zhang

Xuejun Zhang is currently a professor in the School of Electronic and Information Engineering at Beihang University, where he received his BS and PhD degrees in 1994 and 2000, respectively. He is also the deputy director of the National Key Laboratory of CNS/ATM in China. His main research interests are air traffic management, data communication, and air surveillance.

Jian Wei

Wei Jian received his PhD degree in aerospace engineering from Purdue University. He is currently a student member of the AIAA and the IEEE. His research interests lie in dynamic airspace configuration for en route and terminal airspaces, linear and integer programming with applications to air traffic management and airspace configuration under uncertain weather conditions, optimal control with applications to aircraft conflict resolution, multi-body orbital dynamics and control, and deep space exploration.

Inseok Hwang

Inseok Hwang received his PhD degree in aeronautics and astronautics from Stanford University, and is currently an associate professor in the School of Aeronautics and Astronautics at Purdue University. His research interests lie in modelling, estimation, and control of cyber-physical systems (CPS) using the hybrid systems approach and their applications to safety critical systems such as aircraft/spacecraft/unmanned aerial systems, air traffic management, and multi-agent systems. For his research, he leads the Flight Dynamics and Control/Hybrid Systems Laboratory at Purdue University. He received the NSF CAREER award in 2008, was selected as one of the nation's brightest young engineers by the National Academy of Engineering (NAE) in 2008, and also received the AIAA Special Service Citation in 2010. He is an associate fellow of AIAA, and a member of the IEEE Control Systems Society and the IEEE Aerospace and Electronic Systems Society. Currently he is also an associate editor of the IEEE Transactions on Aerospace and Electronic Systems and the Asian Journal of Control, and a conference editorial board member of the IEEE Control Systems Society.

Yanbo Zhu

Yanbo Zhu received his PhD degree from Beihang University. He joined the Aviation Data Communication Corporation (ADCC) in China in 1996 when the company was founded, and now he is the vice president of ADCC. His major research fields include air–ground broadband communication, satellite navigation, collaborative surveillance, and air traffic management.

Kaiquan Cai

Kaiquan Cai received his PhD degree at Beihang University in 2013, and is currently a lecturer in the School of Electronic and Information Engineering at Beihang University. His specialty is traffic information and control engineering and his research interests include airspace design and air traffic optimisation.