The DLR project City-ATM is investigating the integration of uncrewed aerial vehicles in urban environments.
Today we’re at Cochstedt Airport to conduct the demonstration of phase three.
Today we’re flying our DexHawk research drone. We usually plan the flight path of the DexHawk from the ground control station.
What is new now is that we have new features on board the drone and it can travel autonomously in this area of dense traffic.
Cochstedt info – we would like to start now.
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In our experiment today, we will launch several drones to create conflicts and then test whether they recognise each other and stop or move out of the way.
The drones send positional data to German Air Traffic Control, like all other airborne objects in Germany.
All air traffic data are collected there; our ground station then receives this data and can pass it on to the drone.
So our test drone knows where all the other drones in the vicinity are. This means it can conduct avoidance manoeuvres accordingly.
For the next test we don’t have enough drones so we simulate them using a dedicated simulator.
This simulator also sends the positional data for the virtual drones to German Air Traffic Control.
They are not even aware that these are virtual drones and thus treat them like actual drones.
This means we have a higher traffic density and can create more conflicts.
Since the drone can calculate its own flight path and those of other users in advance, it can detect dangerous
situations ahead of time and thus avoid them safely and efficiently at an early stage.
Now, what do we do with obstacles that cannot move out of the way,
such as buildings, trees, flagpoles – that do not report their position on their own, so to speak.
We must detect them somehow. We use LIDAR sensors for this.
In principle, LIDAR sensors use lasers to measure distance.
They can be used to detect objects and visualise them in a 3D image as well as enter their position on the map.
Once the drone has detected an obstacle using the LIDAR sensors, it can also avoid this object.
In phase three we have demonstrated that the drone can autonomously and efficiently navigate through dense airspace.
With the completion of the City-ATM project, we have demonstrated various concepts that other initiatives
can of course use in the future, and which will help to integrate drone transport safely and efficiently.