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Applied Game Theory to Enhance Air Traffic Control in 3D Airspace

Author

Listed:
  • Alireza Rangrazjeddi

    (University of Oklahoma)

  • Andrés D. González

    (University of Oklahoma)

  • Kash Barker

    (University of Oklahoma)

Abstract

The popularity of air transportation, both for personal and commercial uses, has been growing in recent years. As a result, the traffic volume in the airspace is constantly increasing, which leads to the higher chances of conflicts among aircraft. In air traffic management, conflict detection and resolution are challenging and stressful tasks due to the highly dynamic nature of aircraft flight plans as well as the interdependency among pilots’ decisions. Therefore, reliable and comprehensive decision-making techniques are necessary to deal with such conflicts in the airspace in a timely manner. In this regard, innovative technological developments are essential to assist decision-makers. In this paper, we propose a semi-decentralized, three-stage algorithm based on game theory to resolve potential conflicts among multiple aircraft traveling in a 3D shared airspace. The result from the algorithm shows that deviation costs are highly sensitive to the level of congestion in the airspace. The proposed algorithm provides useful information for air traffic control and pilots to enhance their coordination and facilitate decision-making procedures in scenarios with single and multiple conflicts during both nominal and deviated-from-nominal situations.

Suggested Citation

  • Alireza Rangrazjeddi & Andrés D. González & Kash Barker, 2023. "Applied Game Theory to Enhance Air Traffic Control in 3D Airspace," Journal of Optimization Theory and Applications, Springer, vol. 196(3), pages 1125-1154, March.
    • Handle: RePEc:spr:joptap:v:196:y:2023:i:3:d:10.1007_s10957-023-02165-9
    DOI: 10.1007/s10957-023-02165-9
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    References listed on IDEAS

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    1. T. Tarnopolskaya & N. Fulton, 2010. "Synthesis of Optimal Control for Cooperative Collision Avoidance for Aircraft (Ships) with Unequal Turn Capabilities," Journal of Optimization Theory and Applications, Springer, vol. 144(2), pages 367-390, February.
    2. A. Miele & T. Wang & J. A. Mathwig & M. Ciarcià, 2010. "Collision Avoidance for an Aircraft in Abort Landing: Trajectory Optimization and Guidance," Journal of Optimization Theory and Applications, Springer, vol. 146(2), pages 233-254, August.
    3. Diao, Xudong & Chen, Chun-Hsien, 2018. "A sequence model for air traffic flow management rerouting problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 15-30.
    4. Karel Joris Bert Lootens & Marina Efthymiou, 2019. "The Adoption of Network-Centric Data Sharing in Air Traffic Management," Information Resources Management Journal (IRMJ), IGI Global, vol. 32(3), pages 48-69, July.
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