# Sensors and Communication Simulation for Unmanned Traffic Management
###### 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. U  
A 2021 21 927  
with the consequent risk to the population on the ground. Other serious incidents include flying in sensitive and restricted areas such as nuclear power plants or military bases, intentionally or unintentionally. Finally, we cannot rule out in-air incidents caused by either malfunctioning aircraft or pilot's errors that may lead to damage to people and property. The operational concept defined for the safe use of drones seeks the total integration of manned and unmanned aircraft over the same airspace [7]. Nonetheless, traditional air traffic management (ATM) systems are highly dependent on the human factor, which conflicts with the inherent automation of drone operations. Apart from this, ATM systems would be unable to scale to cover the high number of operations that are expected in the future. Therefore, it is evident that it is necessary to develop new control systems that allow the efficient concurrent operation of UAVs while guaranteeing the safety of the rest of the aircraft and the citizens. These new systems are known as unmanned traffic management (UTM) systems. Formally, a UTM system is a set of digitized and highly automated services designed to allow a high number of drones to access airspace safely and efficiently [8]. The definition of services to be provided to users within UTM is currently under discussion, with different potential architectures [9]. In all of them there will be a collection of services provided to the airspace users (drone operators and pilots) and to authorities (law enforcement, emergency, etc.) by either a central entity (i.e., an air navigation service provider, ANSP), or by a collection of UTM service providers (USPs), working collaboratively. A summary of the intended services to be provided is detailed in Table 1, taken (and summarized) from the European SESAR2020 U-Space documentation [10]. The table also shows the associated target time for services launch, in four phases called U1, U2, U3, and U4. In other words, a UTM system is a system of systems where the aforementioned entities interact and exchange information to enable routine drone operations. These interactions can be divided into two large groups: pre-flight interactions and in-flight interactions. In the first group, the authorization process is vital so that the UTM system