What are UTM and SORA anyway?
The idea of fully automated flying drones (UAVs) is an exciting vision, especially when you think of the many possible uses of these flying tools. To make this vision a reality, controlled airspace and digitized approval processes, including a risk assessment, are needed. The challenge for such a system is a technical infrastructure and an ecosystem that enables software-based control of drones in low altitude airspace. Within the framework of the development of a UAS (Unmanned Aircraft Systems) Traffic Management (UTM), the following areas will emerge:
- the identification of new services
- the clarification of roles and responsibilities
- the definition of interfaces, protocols, and standards
- the definition of performance prerequisites
This results in a system of various systems that must be interconnected and not created as a central data platform. This is a concept that helps to integrate drones into airspace and avoid risks. However, a final definition of a UTM is not possible at this time.
In order to establish rules for assessing the risk of drone operations, a future UTM should also be SORA-compatible. SORA (Specific Operations Risk Assessment) is a method for risk assessment of UAS operations. It is suitable for authorities and operators of UAVs and is derived from the Holistic Risk Model (HRM). The approval processes will also be based on this model. In October 2017, the General Principles were laid down in NfL 1-1163-17. For the first time, the risk assessment according to SORA-GER became a condition for the approval of an ascent permit. The soil risk class (GRC) and the air risk class (ARC) are calculated.
Use Case – Challenges in a real scenario
In order to better understand the requirements for a SORA-compatible UTM, the example of tissue transport by drone in urban space is presented. Currently, the city of Hamburg is planning a project to transport tissue samples between hospitals. The picture shows fictitious airspace in which a drone has to fly between two objects (red circles). A direct flight route is not possible due to restrictions. This means that similar to vehicles on the ground, drones can only fly certain routes. This requires technologies that allow communication between the drone and the control center, which controls the drone operations and between the drones themselves.
In the vision, the target for the drone is specified by a location-independent control center. A planning tool is used to suggest the shortest route for the drone to the control station commander and he confirms this. In the background, the software has calculated all no-fly zones, conditions, and altitude data and processed temporary flight restrictions, e.g. from rescue missions, from a database. The pilot and the available drones are stored with their respective specifications in an administration center. The system knows from the stored data and the comparison with an official database that the pilot has the appropriate proof of knowledge. It plans the flight route automatically and determines the respective regulatory requirements. With the help of radio links and digital networks, the drones can also receive information and instructions during the flight. Some of these are processed directly on the device. It is also important that the drones can communicate with each other so that they can coordinate themselves with the help of artificial intelligence (AI) and a mesh network for fast data transmission. With the help of the control console system, the drone operator will be able to track the movements of the UAVs in real time. The aeronautical supervisory authorities and other relevant official institutions will be able to monitor drone missions automatically. They will be able to control airspace coordination by entering no-fly zones, weight, speed or altitude specifications.
What are the 6 key technologies for a functional UTM?
Geo-information is the prerequisite for every planned drone flight. Before each flight, the requirements and regulations for the planned airspace must be checked and validated. In contrast to classical air traffic, drones are often located in ground-level airspace (up to 500ft), which results in special regulations due to ground-based infrastructure. The map of FlyNex shown in the picture shows the requirements which exist due to the respective local conditions. The ground-based infrastructure data account for 90% of the influencing factors for a drone flight up to 500ft.
This means that a large amount of data has to be processed and updated. FlyNex updates its maps daily to provide users with as much up-to-date and accurate information as possible.
This comprehensive geo-information is also necessary in order to carry out a SORA calculation. Then the risk class of the operation is determined. For the determination of the Ground Risk Class (GRC), the existence and validity of the data is an important prerequisite. The geo-information must, therefore, be carefully stored with attributes and metadata.
As described above, a future UTM will be a system of systems. Many systems and different market participants and authorities will have to work together across national borders. At present, many market players are trying to connect other market participants to their individual solutions in a centralized approach. Due to the large number of participants in such a system and their different interests, it is unlikely that anyone will surrender their data sovereignty to a company or a consortium of companies.
The system of a blockchain takes up exactly this problem. Many people only know the blockchain technology from cryptocurrencies. But there are many other applications. Traceable and non-modifiable transactions can be carried out via the decentralized network. This means that the blockchain technology creates the prerequisite that different participants can network in a UTM and work collaboratively without having to give up their data sovereignty. In times when data is described as the oil of the 21st century, the existence of data sovereignty is particularly important for the success of a system with many stakeholders.
The blockchain infrastructure is also considered to be audit-proof and thus offers the possibility of integrating an audit-proof SORA process into a functional UTM. This will be a prerequisite for official recognition and conformity.
By outsourcing the processes to the cloud, the advantages of this scalable, demand-oriented and secure technology can be exploited.
This flexibility becomes more and more relevant for many companies as the amount of data increases. According to the IBM report “10 Key Marketing Trends For 2017”, 90% of existing data has been created in the last two years alone. Of this, approx. 52% is located in the cloud. Large amounts of data are also created for the operation of a UTM, with all processes and stakeholders. These are, for example, airspace data, traffic data, weather data and infrastructure data for ground-based airspace. Cloud computing enables scalable integration and processing of these data sources.
Edge Computing describes the concept of performing more data processing on devices. This reduces the data volume to be transmitted and thus significantly increases the transmission speed (low latency). The technology will be required above all for communication between the ground station and the UAV. It is important that data from the ground station reaches the UAV, the pilot or other clients in milliseconds, e.g. in order to be able to change the flight route. If one imagines that a drone travels at a speed of 43km/h, around 12m per second, one understands the need to work in milliseconds. This is especially true for use in urban areas. On the basis of the geodata and artificial intelligence, the system can independently adapt the navigation and forward and document the information to all participants. This is done without human intervention.
In a mesh network, each node (terminal device) is connected to one or more other nodes (see the picture first from left). The transfer takes place via the individual nodes to the target point. Mesh networks are considered to be very safe, as they continue to function even if individual nodes are omitted, they are self-healing. This provides the prerequisite for safe and reliable communication between drones (see the figure in the middle).
Data entered can be distributed to the drones in question in milliseconds and processed on the onboard unit. This automated and very fast communication between drones prevents their collisions and makes Sense & Avoid technologies superfluous. However, these will probably continue to exist as a redundant system. In pilot tests, the technology is already being used for so-called platooning, s shown in the picture on the right. Vehicles drive in close columns and communicate with each other through a mesh network. They independently regulate the distance and perform driving manoeuvrers.
With the help of artificial intelligence, large amounts of data can be processed in the shortest possible time and decisions can be made automatically on the basis of this data. Depending on the situation, the system understands which information must be made available to which participants in the UTM (drone, pilot, flight control, authorities, etc.). Thus, a system will have to be able to determine the flight routes based on the data provided. This must be done in coordination with all other participants in the airspace and taking into account the requirements of ground-based infrastructure. Due to the large number and complexity of these procedures, a large part of the approval procedures will be automated. This is the only way to coordinate the number of regulated drone missions for a wide variety of applications in the future. Artificial intelligence will be an essential prerequisite for communication between drones. In the event of irregularities, they must be able to react to changes in milliseconds and adapt their own flight routes according to the information provided by other UAVs.
With the LAANC (Low Altitude Authorization and Notification Capability) project, the American FAA has created the first partially automated system for integrating UAVs into airspace. Companies such as SkyWard or AIRMAP have integrated the FAA system into their applications and can automatically apply for ascent approvals for the integrated areas in the system. For certain risk classes, automated approval is then granted, provided all data is validated.
Technologies in the application
An example of the successful integration of some of the presented technologies is the control desk for drones developed by WPS – Workplace Solutions GmbH and FlyNex GmbH. As can be seen in the pictures, drones can be controlled in real time using a large touch screen table based on the FlyNex map data. The control desk can be used to plan operations and monitor the entire mission live. Intervention is possible at any time with a simple finger click. the sensors on the drone record the measurement data and send it directly to the operator. The system has already been used and can be ordered for the corporate integration of unmanned aerospace systems.
The FlyNex Team