Abstract
There has been heightened interest in the application
of unmanned aircraft operations to urban environments in
recent years. This has triggered activities both in the research
communities and private sector to analyze the extent to which
safe, secure and efficient operations can be performed. However,
there is an acute lack of reliable data in this field. BB-Planners
aims to help alleviate this issue. BB-Planner is a simulation tool
developed during the BUBBLES project, funded by the SESAR
Joint Undertaking (SJU), and it is focused on the generation and
analysis of drone traffic in an urban environment. This software
is able to generate trajectories with different patterns of flight
that simulate several types of missions that could occur in an
urban setting, including delivery, surveillance and inspection.
These trajectories can be randomly generated or deconflicted
trajectories defined by their waypoints or areas of operation. The
trajectories generated at this stage are considered ideal, however,
for different applications the degradation generated by the
surveillance system has to be considered. Thus, the BB-planner
tool can inject this degradation, considering the positional errors,
the latency and the probability of detection of the surveillance
system. After the drone trajectories are generated, the system
can count the number of conflicts that occurred during the
simulation. For this end, the value used for the separation minima
can be a single value for all the current drones provided by the
user and based on the total system error (TSE) or a different
value for each drone based both on the TSE and the performance
characteristics of the aircraft. BB-planner can be used to generate
datasets that approximate an airspace with different operators
and evaluate the different parameters¿ effect on the frequency of
conflict and other relevant metrics.
