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Autonomous 4D Trajectory Planning for Dynamic and Flexible Air Traffic Management

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Abstract

With an ever increasing number of unmanned aerial vehicles (UAVs) in flight, there is a pressing need for scalable and dynamic air traffic management solutions that ensure efficient use of the airspace while maintaining safety and avoiding mid-air collisions. To address this need, a novel framework is developed for computing optimized 4D trajectories for UAVs that ensure dynamic and flexible use of the airspace, while maximizing the available capacity through the minimization of the aggregate traveling times. Specifically, a network manager (NM) is utilized that considers UAV requests (including start/target locations) and addresses inherent mobility uncertainties using a linear-Gaussian system, to compute efficient and safe trajectories. Through the proposed framework, a family of mathematical programming problems is derived to compute control profiles for both distributed and centralized implementations. Extensive simulation results are presented to demonstrate the applicability of the proposed framework to maximize air traffic throughput under probabilistic collision avoidance guarantees.

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Funding

This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 739551 (KIOS CoE - TEAMING) and Grant 101003439 (C-AVOID), and by the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.

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Authors and Affiliations

  1. KIOS Research and Innovation Center of Excellence, University of Cyprus, 1678, Nicosia, Cyprus

    Christian Vitale, Savvas Papaioannou, Panayiotis Kolios & Georgios Ellinas

  2. Department of Electrical and Computer Engineering, University of Cyprus, 1678, Nicosia, Cyprus

    Christian Vitale, Savvas Papaioannou, Panayiotis Kolios & Georgios Ellinas

Authors
  1. Christian Vitale
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  2. Savvas Papaioannou
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  3. Panayiotis Kolios
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  4. Georgios Ellinas
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All authors contributed to the study conception and design in equal manner. Material preparation, analysis and implementation was performed by Christian Vitale and Savvas Papaioannou.

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Correspondence to Christian Vitale.

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This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 739551 (KIOS CoE - TEAMING) and Grant 101003439 (C-AVOID), and by the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.

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Vitale, C., Papaioannou, S., Kolios, P. et al. Autonomous 4D Trajectory Planning for Dynamic and Flexible Air Traffic Management. J Intell Robot Syst 106, 11 (2022). https://doi.org/10.1007/s10846-022-01715-z

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