Dynamic collision avoidance using local cooperative airplanes decisions


In the near future, air traffic control (ATC) will have to cope with a radical change in the structure of air transport [1]. Apart from the increase in traffic that will push the system to its limits, the insertion of new aerial vehicles such as drones into the airspace, with different flight performances, will increase its heterogeneity. Current research aims at increasing the level of automation and partial delegation of the control to on-board systems. In this work, we investigate the collision avoidance management problem using a decentralized distributed approach. We propose an autonomous and generic multi-agent system to address this complex problem. We validate our system using state-of-the-art benchmarks. The results underline the adequacy of our local and cooperative approaches to efficiently solve the studied problem.

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The authors thank Sopra Steria Group and the ANRT for their support in this research work.


This work was supported by the Association Nationale de la Recherche et de la Technologie (Grant no. 2016/0940).

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Correspondence to Augustin Degas.

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Degas, A., Rantrua, A., Kaddoum, E. et al. Dynamic collision avoidance using local cooperative airplanes decisions. CEAS Aeronaut J 11, 309–320 (2020). https://doi.org/10.1007/s13272-019-00400-6

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  • Trajectory optimization
  • Automation strategies
  • Conflict resolution
  • Self-separation
  • Multi-agent systems
  • Self-organization