Automatic drone demand generation and evaluation

Abstract

This project consists in building a drone traffic generator capable of spawning random operations in a country. This document provides the guidelines to generate the operations taking into account the existing regulation, the forbidden flight zones, the number of operators and the concept of operations. Using the input parameters, the generator creates and assigns a fleet of drones to each operator introduced. Then, the generator spawns the operations and assigns them to drones, so that each operator has a fleet of drones and list of operations to perform. Furthermore, the operations have an assigned flight schedule to follow the typical workday of the country. The generator also allows visualizing the operations along the day by using the program Google Earth. Moreover, the conflicts and busy areas can also be seen with this program, so that the user can see where they occur. On the other hand, the generated operations are stored in two types of file. The first type corresponds to the XML files, which store the whole information relative to the operators, their fleet of drones and the operations performed by each one. The second type of file corresponds to the MavLink files. These files store the flight plans of all the generated operations. By using the simulator ArduPilot and the software Software in the Loop, the operations can be simulated to obtain the logs. These logs can be used to evaluate, for example, the implementation of ADS-B in drones. Finally, the generator allows changing the parametrization of routes in each simulation, as well as the number of operators and the drone models. Hence, the user is able to see the evolution of drone traffic with the generations. Moreover, the generator allows downloading CSV and XML files, where all the information relative to the generated operations, the assigned fleet of drones and the operators is collected.

Original document

The different versions of the original document can be found in:

• http://hdl.handle.net/2117/108168 under the license http://creativecommons.org/licenses/by-nc-sa/3.0/es/