UTSim: A framework and simulator for UAV air traffic integration, control, and communication

Al-Mousa, Amjed; Sababha, Belal H.; Al-Madi, Nailah; Barghouthi, Amro; Younisse, Remah

doi:10.1177/1729881419870937

Cited by 50 publications

(26 citation statements)

References 41 publications

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“…Simulation of C2 and V2V communications is presented in [ 23 ], where a simulation tool based on the Unity platform is proposed. This tool models aircraft specification, navigation, control, communications between different drones, and sense and avoid systems.…”

Section: Related Workmentioning

confidence: 99%

Sensors and Communication Simulation for Unmanned Traffic Management

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Bergesio

et al. 2021

Sensors

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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.

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Section: Related Workmentioning

confidence: 99%

Sensors and Communication Simulation for Unmanned Traffic Management

Carramiñana

Campaña

Bergesio

et al. 2021

Sensors

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“…Recent publications also present the declarative modelling based models, which enable for constraint programming problem formulation [10,11,13,31,32]. The abovementioned formal methods are supplemented by simulation tools, such as flight simulators [33,34].…”

Section: Literature Reviewmentioning

confidence: 99%

“…To solve the CP defined in formula (33), the values of the decision variables need to be found for which all the constraints are satisfied. By implementing CP in a constraint programming environment, such as IBM ILOG, an answer to the above formulated question is searched.…”

Section: Problem Formulationmentioning

confidence: 99%

Modelling Robust Delivery Scenarios for a Fleet of Unmanned Aerial Vehicles in Disaster Relief Missions

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Golińska-Dawson

Bocewicz

et al. 2021

J Intell Robot Syst

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Besides commercial and military applications, unmanned aerial vehicles (UAVs) are now used more commonly in disaster relief operations. This study proposes a novel model for proactive and reactive planning (different scenarios) that allow for a higher degree of realism, thus a higher likelihood for a mission of being executed according to the plan even when weather forecasts are changing. The novelty of this study results from the addition of a function of resistance of UAVs mission to changes in weather conditions. We link the influence of weather conditions on the UAV’s energy consumption. The goal is to ensure the completion of planned deliveries by a fleet of UAVs under changing weather conditions before their batteries discharge and to identify the emergency route for returned if the mission cannot be completed. An approach based on constraint programming is proposed, as it has proven to be effective in various contexts, especially related to the nonlinearity of the system’s characteristics. The proposed approach has been tested on several instances, which have allowed for analyzing how the plan of mission is robust to the changing weather conditions with different parameters, such as the fleet size, battery capacity, and distribution network layout.

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“…Al-Mousa et al [26] proposed a simulator called UTSim able to simulate different UAV key aspects such as physical specification, navigation, control, communication, sensing, and avoidance in environments with static and moving objects in urban air traffic. The simulator is easy to use and permits specifying a set of parameters: the properties of the environment, the number and types of unmanned aerial vehicles in the environment, and the algorithm to be used for path planning and collision avoidance.…”

Section: Uav/drone Simulatorsmentioning

confidence: 99%

A New FANET Simulator for Managing Drone Networks and Providing Dynamic Connectivity

et al. 2020

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In the last decade, the attention on unmanned aerial vehicles has rapidly grown, due to their ability to help in many human activities. Among their widespread benefits, one of the most important uses regards the possibility of distributing wireless connectivity to many users in a specific coverage area. In this study, we focus our attention on these new kinds of networks, called flying ad-hoc networks. As stated in the literature, they are suitable for all emergency situations where the traditional networking paradigm may have many issues or difficulties to be implemented. The use of a software simulator can give important help to the scientific community in the choice of the right UAV/drone parameters in many different situations. In particular, in this work, we focus our main attention on the new ways of area covering and human mobility behaviors with the introduction of a UAV/drone behavior model to take into account also drones energetic issues. A deep campaign of simulations was carried out to evaluate the goodness of the proposed simulator illustrating how it works.

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UTSim: A framework and simulator for UAV air traffic integration, control, and communication

Cited by 50 publications

References 41 publications

Sensors and Communication Simulation for Unmanned Traffic Management

Sensors and Communication Simulation for Unmanned Traffic Management

Modelling Robust Delivery Scenarios for a Fleet of Unmanned Aerial Vehicles in Disaster Relief Missions

A New FANET Simulator for Managing Drone Networks and Providing Dynamic Connectivity

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