# Unmanned Aerial Traffic Management System Architecture for U-Space In-Flight Services
## 6 Conclusions  
In this paper, we have presented a UTM system architecture framed within the U-space ecosystem. Our software architecture is flexible and general, and it is built as an open-source solution that could be easily extended with additional U-space functionalities. Nonetheless, we have focused on in-flight services for automated threat management and conflict resolution, which is a major gap in the current state of the art. In our realistic experimental setup, with the involved systems running HITL simulations communicated through a remote link with the UTM system, we have demonstrated that the proposed UTM solution is capable of managing unexpected events in real time, proposing solutions in an automated manner. In our experiments, the system was able to detect and resolve different types of conflicts, reasoning about 4D UAS trajectories and Operational Volumes. Besides, we have tested the feasibility of the system for the future U-space, integrating heterogeneous types of UAS (fixed and rotary wing), heterogeneous positioning technologies (ADS-B and telemetry from different autopilots), and a database to keep track in real time of the different UAS operations and geofences. Our system has still some practical limitations. First, it relies on a centralized UTM server that requires continuous communication with the other actors. This bottleneck could be addressed by splitting the UTM system into a set of distributed and interconnected servers. Second, our approach does not consider non-cooperative vehicles in the VLL airspace, such as ultralight planes, nor pre-flight services. However, the architecture is flexible enough to integrate additional services, e.g., for flight operation pre-planning. Besides, non-cooperative vehicles could be tackled by working with see&avoid systems on board the UAS. As future work, we plan to develop further on the emergency management functionality, analyzing the possible threats that could appear in the VLL airspace,  
Figure 19: A top (**left**) and a perspective (**right**) view of the optimal solution in the use case 2. An alternative flight plan for UAS\({}_{2}\) is generated to avoid the geofence. Figure 18: (**Left**), top view with the initial flight plans in the use case 2. The Operational Volumes without conflicts are also shown. (**Right**), situation after the detection of the jamming attack. A geofence (in red) is created around the attacked UAS, which generates a conflict with the flight plan of the other UAS. and quantifying the involved risks of the alternative solutions proposed by our system. Thus, we will be able to improve the capabilities of the system to solve more conflicts safely and efficiently, and to test it in more varied use cases. Furthermore, we plan to adapt our UTM system to ROS 2 and to validate it in field trials within the framework of the GAUSS project, which will be a significant step toward a totally automated U-space environment. Conceptualization, C.C., A.C. and J.C.; software and validation, C.C. and H.P.-L.; writing and editing, C.C., H.P.-L. and J.C.; supervision, A.C., J.C. and A.O. ; funding acquisition, A.O. All authors have read and agreed to the published version of the manuscript. This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No 776293 (GAUSS). Not applicable. The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author. The authors declare no conflict of interest. The following abbreviations are used in this manuscript: