IEEE - Aerospace and Electronic Systems - May 2023 - 70

Live Trials of Dynamic Geo-Fencing for the Tactical Avoidance of Hazard Areas
The drones autonomously detected separation violation
between own position and uplinked geo-fence and
changed their mode to predefined position hold. This is
a reasonable solution for the drone 3 trying to penetrate
the geo-fence from the outside. Drone 1, which was
already flying within the geo-fence, needs further
instructions from ground to evacuate the fence, because
no collision avoidance functionality was installed on
the drone.
Detection of conflicts based on own forecasted trajectory
instead of using own position would allow a forecast
of separation violations in the near future, and allow early
reaction. Furthermore, an onboard conflict resolution
module would allow drone 1 to evacuate the geo-fence
autonomously, in best case also considering all other
NFZs and trajectories from surrounding traffic. Both trajectory-based
conflict detection and onboard resolution
will be a part of the phase 3 demonstration.
SUMMARY AND OUTLOOK
This article describes the City-ATM phase 2 demonstrations
that focused on the creation of dynamic geo-fences
around a danger spot. The final demonstration on October
1st proved that the concept is feasible in practice. The
lack of an onboard trajectory-based CD&R module has
been identified as major shortcoming.
Phase 3 will have a strong focus on complex traffic scenarios.
Since the number of available physical drones is
limited, some real drones will be operated together with a
large number of virtual drones operated by a simulator.
Base for phase 3 will be the software and hardware setup
described here. It will be extended with 4-D capabilities,
allowing to predict and follow 4-D trajectories with high
precision. That way, separation violations can be detected
and avoided well in advance, including the penetration of
geo-fences. Besides being controlled from ground control
station, drones can also operate board-autonomously.
Among others, following functionalities are added to the
existing system for phase 3.
Drones will have a new 4-D guidance module on
board, developed by DLR. Drones will be able to
follow 4-D trajectories. The module will be integrated
using a companion computer.
Trajectory predictor and CD&R functionality that
already exists in the GCS will also be integrated on
board.
An onboard mission manager and above-mentioned
modules will allow the drones to fly autonomously
in a complex traffic scenario.
Two onboard Lidar sensors allow detection of noncooperative
vehicles.
70
E-Identification from phase 1 will be extended.
Virtual traffic will be fed into DFS's tracking server
to achieve a deep integration.
Drones can either be controlled via the U-Fly, or
drones can be put into autonomous mode.
The BVLOS functionality from phase 1 will be refined.
REFERENCES
[1] D. Geister and B.Korn, " Concept for urban airspace integration
DLR U-Space blueprint, " German Aerosp. Center -
Inst. Flight Guid., Braunschweig, Germany, 2017. [Online].
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[2] S. Kern, D. Geister, and B. Korn, " City-ATM-Demonstration
of traffic management in urban airspace in case of
bridge inspection, " in Proc. 38th Digit. Avionics Syst.
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[3] DLR, " Interaktion von Drohnen in St€adten-das Projekt
City-ATM, " 2019. [Online]. Available: https://www.
youtube.com/watch?v¼AJwB2LBD6m8&t¼33s
[4] Airservice Australia, " Safe operations around controlled
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airservicesaustralia.com/wp-content/uploads/15-0905FACSafety-Net-Safe-Operations.pdf
[5]
G. Zhu and P. Wei, " Low-altitude UAS traffic coordination
with dynamic geofencing, " in Proc. 16th AIAA Aviation
Technol., Integration, Operations Conf., 2016, pp. 1-12,
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[6] M. N. Stevens and E. M. Atkins, " Geofencing in immediate
reaches airspace for unmanned aircraft system traffic
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[7] V. Alarcon et al., " Procedures for the integration of drones
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[8] R. M. Geister, L. Limmer, M. Rippl, and T. Dautermann,
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IEEE A&E SYSTEMS MAGAZINE
MAY 2023

https://www.dlr.de/content/de/downloads/2017/blueprint-concept-for-urban-airspace-integration_2933.pdf?__blob=publicationFile&v=11 https://www.dlr.de/content/de/downloads/2017/blueprint-concept-for-urban-airspace-integration_2933.pdf?__blob=publicationFile&v=11 https://www.dlr.de/content/de/downloads/2017/blueprint-concept-for-urban-airspace-integration_2933.pdf?__blob=publicationFile&v=11 http://dx.doi.org/10.1109/DASC43569.2019.9081663 http://dx.doi.org/10.1109/DASC43569.2019.9081663 https://www.youtube.com/watch?v=AJwB2LBD6m8&t=33s https://www.youtube.com/watch?v=AJwB2LBD6m8&t=33s https://www.airservicesaustralia.com/wp-content/uploads/15-0905FAC-Safety-Net-Safe-Operations.pdf https://www.airservicesaustralia.com/wp-content/uploads/15-0905FAC-Safety-Net-Safe-Operations.pdf https://www.airservicesaustralia.com/wp-content/uploads/15-0905FAC-Safety-Net-Safe-Operations.pdf http://dx.doi.org/10.2514/6.2016-3453 http://dx.doi.org/10.2514/6.2018-2140 https://doi.org/10.3390/aerospace7090128 http://dx.doi.org/10.1109/ICNSURV.2018.8384845 http://elib.dlr.de/98476/1/dissKuenzS.pdf http://elib.dlr.de/98476/1/dissKuenzS.pdf http://dx.doi.org/10.1177/0954410015613113

IEEE - Aerospace and Electronic Systems - May 2023

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