Abstract
Unmanned traffic management (UTM) systems will become a key enabler to the future drone market ecosystem, enabling the safe concurrent operation of both manned and unmanned aircrafts. Currently, these systems are usually tested by performing real scenarios that are costly, limited, hardly scalable, and poorly repeatable. As a solution, in this paper we propose an agent-based simulation platform, implemented through a micro service architecture, which may simulate UTM information sources, such as flight plans, telemetry messages, or tracks from a surveillance network. The final objective of this simulator is to use these information streams to perform a system-level evaluation of UTM systems both in the pre-flight and in-flight stages. The proposed platform, with a focus on simulation of communications and sensors, allows to model UTM actors’ behaviors and their interactions. In addition, it also considers the manual definition of events to simulate unexpected behaviors/events (contingencies), such as communications failures or pilots’ actions. In order to validate our architecture, we implemented a simulator that considers the following actors: drones, pilots, ground control stations, surveillance networks, and communications networks. This platform enables the simulation of the drone trajectory and control, the C2 (command and control) link, drone detection by surveillance sensors, and the communication of all agents by means of a mobile communications network. Our results show that it is possible to truthfully recreate complex scenarios using this simulator, mitigating the disadvantages of real testbeds.
Highlights
Unmanned aerial vehicle (UAV) usage has experienced a remarkable expansion in the last decades, thanks to key advancements in the technological domain
It should be possible to generate and simulate a contingency consisting of the loss of link (LOL) between the drone and the ground control station (GCS)
Two possible C2 channels have been considered: (1) A channel established directly between the GCS and the drone that is used in visual line of sight (VLOS)
Summary
Unmanned aerial vehicle (UAV) usage has experienced a remarkable expansion in the last decades, thanks to key advancements in the technological domain. This information may be merged with data from traditional ATM systems (i.e., radar and other air surveillance sensors tracks) and sensors from different drone surveillance networks All these data allow to track drones and conflicting aircraft in real time, while monitoring the safety and conformance with the issued authorization and safety rules of all operations, generating alerts in case of deviations or risks. Non-cooperative drone surveillance sensors may detect drones performing operations that have not been authorized and declared with the UTM ecosystem (non-cooperative drones) This information is key in some use cases, such as detecting unauthorized flights over critical infrastructures or real-time tactical conflict detection with cooperative drones or with manned aircraft. Proposedsimulation simulationframework frameworkand andhigh-level high-level unmanned traffic management simulator integration
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