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Resilient UAV Traffic Congestion Control Using Fluid Queuing Models

Jiazhen Zhou, Li Jin, Xiao Wang, Dengfeng Sun

2020IEEE Transactions on Intelligent Transportation Systems29 citationsDOI

Abstract

In this paper, we address the issue of congestion in future Unmanned Aerial Vehicle (UAVs) traffic system in uncertain weather. We treat the traffic of UAVs as fluid queues, and introduce models for traffic dynamics at three basic traffic components: single link, tandem link, and merge link. The impact of weather uncertainty is captured as fluctuation of the saturation rate of fluid queue discharge (capacity). The uncertainty is assumed to follow a continuous-time Markov process. We define the resilience of the UAV traffic system as the long-run stability of the traffic queues and the optimal throughput strategy under uncertainties. We derive the necessary and sufficient conditions for the stabilities of the traffic queues in the three basic traffic components. Both conditions can be easily verified in practice. The optimal throughput can be calculated via the stability conditions. Our results offer strong insight and tool for designing flows in the UAV traffic system that is resilient against weather uncertainty.

Topics & Concepts

Queueing theoryComputer scienceQueueTraffic generation modelMarkov processTraffic congestion reconstruction with Kerner's three-phase theoryTraffic equationsTraffic flow (computer networking)Traffic congestionDistributed computingReal-time computingComputer networkEngineeringTransport engineeringLayered queueing networkMathematicsStatisticsTraffic control and managementVehicular Ad Hoc Networks (VANETs)Air Traffic Management and Optimization
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