Cooperative conflict detection and resolution and safety assessment for 6G enabled unmanned aerial vehicles

Li, Shanmei ORCID: https://orcid.org/0000-0002-2622-4403, Cheng, Xiaochun ORCID: https://orcid.org/0000-0003-0371-9646, Huang, Xuedong ORCID: https://orcid.org/0000-0002-5094-9041, Otaibi, Sattam AI ORCID: https://orcid.org/0000-0002-7747-4701 and Wang, Hongyong (2023) Cooperative conflict detection and resolution and safety assessment for 6G enabled unmanned aerial vehicles. IEEE Transactions on Intelligent Transportation Systems, 24 (2) . pp. 2183-2198. ISSN 1524-9050 [Article] (doi:10.1109/tits.2021.3137458)

Abstract

The increasing number of Unmanned Aerial Vehicles (UAVs) in the low-altitude airspace and the increasing complexity of the work environment present new challenges for ensuring airspace security, especially the effective conflict detection and resolution (CD&R) of UAVs. In the era of the sixth generation (6G) technology, there is an improvement in communication speed and capacity in comparison with the traditional communication technologies, which contributes to forming a UAV Internet of Things (IoTs) through remote intelligent control platform and improve the effect of CD&R. In this paper, we innovatively develop a cooperative CD&R method in the UAV IoT environment considering UAV relative motion relationships and UAV priorities. Using this method in 6G environment, the real-time and reactive conflict-free paths for UAVs can be generated. The developed method has the advantage of smaller calculation and needs fewer UAVs to take maneuvers than the CD&R methods based on traditional Artificial Potential Field (APF). To verify the effectiveness of CD&R methods, a safety assessment method (evaluate from both conflict feature and network structure perspectives) is also proposed. A Monte Carlo Simulation with ``clone mechanism'' is designed to incorporate the effect of CD&R systems. Three cases of distributed CD&R protocols are simulated and compared. The simulations with different parameter settings are also discussed. Quantitative simulation experiments show that the safety effect of CD&R proposed in this paper is improved a lot due to the improved APF and the UAV priority determination. Meanwhile, the safety assessment method is demonstrated to be feasible for evaluating the safety of CD&R systems.

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