Periodic Reporting for period 1 - USEPE (U-space Separation in Europe)
Reporting period: 2021-01-01 to 2021-12-31
USEPE contributes to the advance of U-space services to enable the safe and efficient operations of a large number of drones, without adversely affecting manned aviation by ensuring safe separation management of drones through the relevant flight planning management and de-confliction.
USEPE will bring clear benefits for the society in several ways. From the economic point of view, safe drone flights in urban environments will open up a new range of business applications and opportunities, thus creating new jobs. In addition, in the regulatory dimension, the outcomes of USEPE will provide important feedback to the aviation authorities or policy makers regarding the airspace structure management. Moreover, the use of artificial intelligence techniques is not sufficiently extended in a traditional sector such as aviation and USEPE results will provide a better understanding in this area.
Thus, the USEPE outcomes will clearly be used in the development of future regulations and Acceptable Means of Compliance.
U-space- and ATM-users such as entities planning to use drones for new commercial purposes and innovative ideas, drone operators, manufacturers will benefit as well.
A major beneficiary of USEPE results will be cities where drone operations will happen. Thanks to USEPE they will gain confidence in the safety of drone operations and will see more and more opportunities to enhance the services they provide to citizens.
Civil society is the ultimate beneficiary of the project, as the enhanced methods provided by USEPE will enable drones to fly safely without the risk for collisions with other drones or manned aircraft.
The goal of USEPE is to propose, develop and evaluate a Concept of Operations and a set of enabling technologies aimed at ensuring the safe separation of drones (from each other and from manned aviation) in the U-space environment, with particular focus on densely populated areas.
In order to achieve this goal, four specific objectives have been identified:
• Identify who shall be the predetermined separator (the drones themselves or the U-space systems) throughout the strategic and tactical planning phases.
• Define and simulate a set of concepts to provide safe separation for different kind of drones in each planning phase.
• Assess the impact of the proposed concepts on different Key Performance Areas (KPAs), in particular on safety, capacity and efficiency, in order to derive conclusions and recommendations on the most adequate approach for each operational environment.
• Disseminate the project results to all concerned stakeholders in order to collect their feedback regarding the appropriateness of the transition to the subsequent stages of the R&I cycle.
The project is working to obtain a Validated Operational Concept for the safe operation of drones in urban areas. For this purpose, USEPE project has produced Deliverable D3.1 “Concept of Operations Outline” based on the stakeholders’ needs and requirements.
USEPE ConOps introduces a new separation method named “Dynamic Density Corridor Concept” (D2-C2) which combines Dynamic segments based on traffic density, high-speed corridors with lower conflict risk and general geovectoring syntax.
In order to test the USEPE concept of operations and to validate the new concept D2-C2, three different scenarios have been identified: last mile delivery, emergency operations and urban surveillance operations. Hannover city has been selected to validate these scenarios.
The project has been working on the implementation of the Design Concept:
• A literature review was conducted to identify the most suitable simulation environment for the analysis of drone traffic management in urban areas.
• As a result, the project decided to use BlueSky, an open-source simulation environment developed in Python.
• A module related to import turbulent wind field data in the BlueSky simulator has been developed.
The USEPE project is implementing new functionalities to BlueSky to simulate the D2-C2 separation method and its effects on the urban drone traffic.
The project is also working on the use of Machine Learning approach to improve the separation management of drones. An initial set of suitable machine learning algorithms have been identified and will be included in D4.2 “Initial Report on Machine Learning Algorithms”.
The Validation Plan was handed over to SJU as formal Deliverable (D5.1) and approved. 18 Validation Objectives have been identified.
The preparation of the simulation environment involves the development of new modules in BlueSky: City module, path planning module, strategic deconfliction module and a module to divide airspace into segments.
Any new development will be shared with the research community through a public repository. The project is elaborating a complete user manual of BlueSky’s new features.
Another thing to remark about USEPE Project, is the application of Machine Learning algorithms in order to improve the separation management. During this reporting period, suitable tools, platforms and libraries were identified, also the “Neural Network” algorithm is selected as the most promising.
Finally, the use of accurate wind conditions that occur specifically in the city environment is deemed to be beyond the-state-of-the-art.
For all the above reasons, cities, citizens and drone operators will be the main beneficiaries of USEPE results. But also the research community will benefit from USEPE achievements, thanks to the new developments in BlueSky simulator and the results from Machine Learning Algorithms applied to automate the Separation Management service.