  Unmanned Aerial Vehicles (UAVs), in particular Drones, have gained
significant importance in diverse sectors, mainly military uses. Recently, we
can see a growth in acceptance of autonomous UAVs in civilian spaces as well.
However, there is still a long way to go before drones are capable enough to be
safely used without human surveillance. A lot of subsystems and components are
involved in taking care of position estimation, route planning, software/data
security, and collision avoidance to have autonomous drones that fly in
civilian spaces without being harmful to themselves, other UAVs, environment,
or humans. The ultimate goal of this research is to advance collision avoidance
and mitigation techniques through quantitative safety risk assessment. To this
end, it is required to identify the most relevant faults/failures/threats that
can happen during a drone's flight/mission. The analysis of historical data is
also a relevant instrument to help to characterize the most frequent and
relevant issues in UAV systems, which may cause safety hazards. Then we need to
estimate their impact quantitatively, by using fault injection techniques.
Knowing the growing interests in UAVs and their huge potential for future
commercial applications, the expected outcome of this work will be helpful to
researchers for future related research studies. Furthermore, we envisage the
utilization of expected results by companies to develop safer drone
applications, and by air traffic controllers for building failure prediction
and collision avoidance solutions.
