U-space Separation in Europe

Project Information

USEPE

Grant agreement ID: 890378

DOI

10.3030/890378

Project closed

EC signature date 30 October 2020

Start date 1 January 2021

End date 31 December 2022

Funded under

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Total cost

€ 1 999 308,75

EU contribution

€ 1 999 308,75

Coordinated by

INGENIERIA DE SISTEMAS PARA LA DEFENSA DE ESPANA SA-SME MP
Spain

Periodic Reporting for period 2 - USEPE (U-space Separation in Europe)

Reporting period: 2022-01-01 to 2022-12-31

Summary of the context and overall objectives of the project

The main problem to be addressed in this project is to solve the growing demand for drones in densely populated areas, without compromising safety while taking into consideration turbulent wind shear.
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.
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.
As a conclusion of the Action, USEPE solution can be summarise as follows:
USEPE-SOL consists of a new separation method for drones in the urban environment, the Dynamic Density Corridor Concept (D2-C2), aiming 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. The method relies on three pillars:
• Segments are 3D volumes, each one with its own parameters: speed limit, capacity, performance requirements, etc., which are common for every drone flight in a particular segment. Segmentation of the airspace is a dynamic, fast and flexible process.
• High-speed corridors are defined as three-dimensional tubes in space where the drones travel along them in one direction only
• Geovectoring rules are defined for flying both in corridors and segments (minimum and maximum speed, rate of ascent/descent and limits to heading), to manage traffic complexity by reducing the relative velocity between drones, lowering collision risks.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The main achievements of the project since the beginning in 2021 up to December 2022 can be summarised as follows:
Operational Concept
WP3 was entirely devoted to obtain a new Operational Concept. The project has taken a Systems’ Engineering approach collecting the stakeholder needs and requirements through surveys, workshops and conferences and coming back to them to see if after validation their needs were met. The project has elaborated 3 full ConOps, Outline, Initial and Consolidated ConOps. The Consolidated one includes the relevant stakeholders ideas, fellow projects and Advisory Board Members valuable inputs, SJU comments and CORUS-XUAM main concepts applicable to USEPE environment.
Development of Design Concept
The design concepts selected as part of USEPE ConOps Outline were implemented using BlueSky simulation tool. In order to depict a credible picture of Hannover city layout and include all relevant airspace characteristics defined by USEPE D2-C2 the project has adjusted BlueSky as needed. Particularly interesting the adjustments made to include the following concepts:
• Safety volumes are used to obtain segments occupancy and check whether the segments could become overpopulated or there is still room to safely accommodate more drone flights.
• Performance-based conflict detection method computes in advance all possible combinations between ownship velocities, possible intruder velocities and potential avoidance manoeuvres and suggests the optimal resolution manoeuvre to resolve the conflict.
The three validation exercises of USEPE focused on delivery drones, an emergency drone that needs to be prioritized over all other drones, and surveillance drones.
For each of the three exercises, validation scenarios were created for both reference and solution cases. In the reference scenarios, separation was performed by legacy methods, i.e. D2-C2 was not applied. In the solution scenarios, which used the same traffic as the reference scenarios, separation was ensured by applying D2-C2.
Validation results showed that, the D2-C2 method effectively improvs the safety metrics in all the cases analysed: reduction of number of conflicts, and reduction of Loss of Separation and near mid-air collisions events compared with the reference scenarios. This trend became more pronounced the higher the traffic density, showing that the method improved its performance as the traffic becomes more challenging, with reductions of more than a 50% of number of conflicts in the highest traffic density cases.
Overall, the ConOps for the USEPE Solution includes features usable by U-space services and UTM (Unmanned Traffic Management) systems.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

USEPE Solution (the D2-C2 separation method) mainly involves 2 new airspace structures, segments and corridors, and new ways to address the strategic, tactical conflict resolution and dynamic capacity management U-space services.
USEPE Solution can be beneficial at local level and still can be tailored to meet local needs. In that respect the USEPE Solution has made progress beyond the State of the art.
One innovation of the USEPE project has been to consider the effects of high-resolution wind fluctuations within the drone traffic simulations.
For the USEPE exercise scenarios varied meteorological conditions in the city of Hannover (Germany) were considered: the path planning and dynamic segmentation services have taken into consideration these wind effects.
The USEPE project was accompanied by Machine Learning (ML) algorithms placed to detect conflicts between aircraft and to reduce the likelihood of collisions in U-space. Also, the developed algorithm was flexible enough to be applicable beyond U-space.
The algorithm was named USEPE_ML (USEPE Machine Learning algorithm) and made available to the public and implemented in a plugin form for BlueSky ATM simulator.
In order to validate the separation method proposed, a set of software developments were made for the BlueSky simulator. The modules developed and the functionalities they apply are the following:
• City model: Representation of the urban environment.
• Path planning: Calculation of the optimal trajectory for a drone ree of conflicts.
• Airspace dynamic segmentation: Creation of segments that divide the airspace and provision of update rules for modifying their attributes.
• Performance-based conflict detection: Calculation of safety volumes for each pair of drones and the optimal avoidance manoeuvre.
The modules mentioned are reusable for future research in U-space and are publicly available to the research community through the USEPE repository, and the data.
Moreover, the procedure followed and tools proposed can be applied to any urban environment, provided the 3D map of the city, making it scalable to any location worldwide.

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