# Sensors and Communication Simulation for Unmanned Traffic Management
## 3 Comprehensive Simulation Scenarios for UTM Services Validation  
Although the focus of this paper is the simulation of communications and sensors, it is not possible to do so (due to the interrelations explained in Section 1) without simulating comprehensive scenarios also covering drones, pilots, and the environment in which all these actors operate. Therefore, it is necessary to discuss which aspects related to both actors and the environment must be modeled to generate comprehensive simulation scenarios for UTM systems evaluation. It has to be noted that, from the systematic point of view, a detailed modeling of a given actor is only relevant insofar as the changes arising in that level of detail may affect the behavior and results of the UTM system. We can start by identifying the necessary aspects related to drones, as they constitute the main actor within a UTM platform. A comprehensive simulator must be able to reproduce the trajectory followed by a drone as it executes a given operation (defined with a flight plan) but also taking into account other factors such as drone dynamics and meteorology. Drone trajectory is also affected by positioning errors suffered by the drone navigation system and control errors due to the drone's autopilot, which should be taken into consideration too. In order to interact with a UTM system, a simulator must also be able to assign unique identifiers to each of the simulated drones (e-registration function). Finally, drones may also be affected by contingencies related to equipment failures, such as the loss of control (LOC), loss of GPS (LOG), and loss of battery (LOB). However, drones operate at the command of pilots who are in charge of designing the drone operation, submitting a flight plan to the UTM system authorization process, and in some cases manually flying the drone. Our simulator is capable of generating both visual line of sight (VLOS) and beyond visual line of sight (BVLOS) traffic (flights) for different drones within a user-defined geographical area and time frame. Traffic generation also considers different flight priorities that might have an impact on authorization. Afterwards, the simulator emulates the submission of each flight plan to the authorization process. Some pilot decisions can be modeled at this point as contingencies. First, a pilot might decide to fly without submitting a flight plan to the UTM system. Then, it is also possible that the pilot decides not to respect the result of the authorization process performing the operation (flying) even when it has been rejected. Within the flight phase, we find new pilot-related contingencies: the pilot may decide not to respect the approved flight plan and fly following another route or at a different time. Likewise, he can initiate actions such as landing or starting a return-to-home maneuver at any time. In addition, the pilot also decides if the drone will send information periodically to the UTM system (cooperative drone) or not (non-cooperative drone). Moreover, control of the aircraft is not perfect, and the final trajectory followed by the drone might slightly deviate from an ideal one, with a control error which will depend on the pilot's skills or autopilot quality. The C2 communications channel between the GCS and the drone should be simulated both in case of VLOS operations (usually consisting of a direct wireless communication link) and in BVLOS operations (typically making use of mobile communications networks). Through this channel, command sending to the drone and the reception of information about its status must be individually simulated. Furthermore, it should be possible to generate and simulate a contingency consisting of the loss of link (LOL) between the drone and the GCS. Simulating these aspects is vital as a message loss or link interruption can trigger important side effects such as trajectory changes or the disruption of the telemetry sending process.