Galileo and EGNOS as an asset for UTM safety and security

GAUSS (Galileo-EGNOS as an Asset for UTM Safety and Security) is a H2020 project1 that aims at designing and developing high performance positioning systems for drones within the U-Space framework focusing on UAS (Unmanned Aircraft System) VLL (Very Low Level) operations. The key element within GAUSS is the integration and exploitation of Galileo and EGNOS exceptional features in terms of accuracy, integrity and security, which will be key assets for the safety of current and future drone operations. More concretely, high accuracy, authentication, precise timing (among others) are key GNSS (Global Navigation Satellite System) enablers of future integrated drone operations under UTM (UAS Traffic Management) operations, which in Europe will be deployed under U-Space [1]. The U-Space concept helps control, manage and integrate all UAS in the VLL airspace to ensure the security and efficiency of UAS operations. GAUSS will enable not only safe, timely and efficient operations but also coordination among a higher number of RPAS (Remotely Piloted Aircraft System) in the air with the appropriate levels of security, as it will improve anti-jamming and anti-spoofing capabilities through a multi-frequency and multi-constellation approach and Galileo authentication operations. The GAUSS system will be validated with two field trials in two different UTM real scenarios (in-land and sea) with the operation of a minimum of four UTM coordinated UAS from different types (fixed and rotary wing), manoeuvrability and EASA (European Aviation Safety Agency) operational categories. The outcome of the project will consist of Galileo-EGNOS based technological solutions to enhance safety and security levels in both, current UAS and future UTM operations. Increased levels of efficiency, reliability, safety, and security in UAS operations are key enabling features to foster the EU UAS regulation, market development and full acceptance by the society.Peer ReviewedPostprint (author's final draft

Hybrid metaheuristic optimization algorithm for strategic planning of {4D} aircraft trajectories at the continent scale

International audienceGlobal air-traffic demand is continuously increasing. To handle such a tremendous traffic volume while maintaining at least the same level of safety, a more efficient strategic trajectory planning is necessary. In this work, we present a strategic trajectory planning methodology which aims to minimize interaction between aircraft at the European-continent scale. In addition, we propose a preliminary study that takes into account uncertainties of aircraft positions in the horizontal plane. The proposed methodology separates aircraft by modifying their trajectories and departure times. This route/departure-time assignment problem is modeled as a mixed-integer optimization problem. Due to the very high combinatorics involved in the continent-scale context (involving more than 30,000 flights), we develop and implement a hybrid-metaheuristic optimization algorithm. In addition, we present a computationally-efficient interaction detection method for large trajectory sets. The proposed methodology is successfully implemented and tested on a full-day simulated air traffic over the European airspace, yielding to an interaction-free trajectory plan

Air traffic deconfliction using sum coloring

Best of Session (UTM-6: sUAS Traffic Management and Deconfliction) Award, 38 DASC 38th IEEE/AIAA Digital Avionics Systems ConferenceThis paper studies strategic conflict resolution for air traffic based on sum coloring. We consider two application scenarios: manned and unmanned air traffic, with similar targets: to improve efficiency of operations and to reduce the costs. For the Unmanned Air Vehicles Traffic Management (UTM) we consider also a payment mechanism which incentivizes the operators to share information necessary to find a socially optimal solution. We quantify the potential savings via a series of experiments, showing that our methods drastically outperform the widely used First-Come-First-Serve (FCFS) strategy.Peer ReviewedAward-winningPostprint (published version

Contributions to deconfliction advanced U-space services for multiple unmanned aerial systems including field tests validation

Unmanned Aerial Systems (UAS) will become commonplace, the number of UAS flying in European airspace is expected to increase from a few thousand to hundreds of thousands by 2050. To prepare for this approaching, national and international organizations involved in aerial traffic management are now developing new laws and restructuring the airspace to incorporate UAS into civil airspace. The Single European Sky ATM Research considers the development of the U-space, a crucial step to enable the safe, secure, and efficient access of a large set of UAS into airspace. The design, integration, and validation of a set of modules that contribute to our UTM architecture for advanced U-space services are described in this Thesis. With an emphasis on conflict detection and resolution features, the architecture is flexible, modular, and scalable. The UTM is designed to work without the need for human involvement, to achieve U-space required scalability due to the large number of expected operations. However, it recommends actions to the UAS operator since, under current regulations, the operator is accountable for carrying out the recommendations of the UTM. Moreover, our development is based on the Robot Operating System (ROS) and is open source. The main developments of the proposed Thesis are monitoring and tactical deconfliction services, which are in charge of identifying and resolving possible conflicts that arise in the shared airspace of several UAS. By limiting the conflict search to a local search surrounding each waypoint, the proposed conflict detection method aims to improve conflict detection. By splitting the issue down into smaller subproblems with only two waypoints, the conflict resolution method tries to decrease the deviation distance from the initial flight plan. The proposed method for resolving potential threats is based on the premise that UAS can follow trajectories in time and space properly. Therefore, another contribution of the presented Thesis is an UAS 4D trajectory follower that can correct space and temporal deviations while following a given trajectory. Currently, commercial autopilots do not offer this functionality that allows to improve the airspace occupancy using time as an additional dimension. Moreover, the integration of onboard detect and avoid capabilities, as well as the consequences for U-space services are examined in this Thesis. A module capable of detecting large static unexpected obstacles and generating an alternative route to avoid the obstacle online is presented. Finally, the presented UTM architecture has been tested in both software-in-theloop and hardware-in-the-loop development enviroments, but also in real scenarios using unmanned aircraft. These scenarios were designed by selecting the most relevant UAS operation applications, such as the inspection of wind turbines, power lines and precision agriculture, as well as event and forest monitoring. ATLAS and El Arenosillo were the locations of the tests carried out thanks to the European projects SAFEDRONE and GAUSS.Los sistemas aéreos no tripulados (UAS en inglés) se convertirán en algo habitual. Se prevé que el número de UAS que vuelen en el espacio aéreo europeo pase de unos pocos miles a cientos de miles en 2050. Para prepararse para esta aproximación, las organizaciones nacionales e internacionales dedicadas a la gestión del tráfico aéreo están elaborando nuevas leyes y reestructurando el espacio aéreo para incorporar los UAS al espacio aéreo civil. SESAR (del inglés Single European Sky ATM Research) considera el desarrollo de U-space, un paso crucial para permitir el acceso seguro y eficiente de un gran conjunto de UAS al espacio aéreo. En esta Tesis se describe el diseño, la integración y la validación de un conjunto de módulos que contribuyen a nuestra arquitectura UTM (del inglés Unmanned aerial system Traffic Management) para los servicios avanzados del U-space. Con un énfasis en las características de detección y resolución de conflictos, la arquitectura es flexible, modular y escalable. La UTM está diseñada para funcionar sin necesidad de intervención humana, para lograr la escalabilidad requerida por U-space debido al gran número de operaciones previstas. Sin embargo, la UTM únicamente recomienda acciones al operador del UAS ya que, según la normativa vigente, el operador es responsable de las operaciones realizadas. Además, nuestro desarrollo está basado en el Sistema Operativo de Robots (ROS en inglés) y es de código abierto. Los principales desarrollos de la presente Tesis son los servicios de monitorización y evitación de conflictos, que se encargan de identificar y resolver los posibles conflictos que surjan en el espacio aéreo compartido de varios UAS. Limitando la búsqueda de conflictos a una búsqueda local alrededor de cada punto de ruta, el método de detección de conflictos pretende mejorar la detección de conflictos. Al dividir el problema en subproblemas más pequeños con sólo dos puntos de ruta, el método de resolución de conflictos intenta disminuir la distancia de desviación del plan de vuelo inicial. El método de resolución de conflictos propuesto se basa en la premisa de que los UAS pueden seguir las trayectorias en el tiempo y espacio de forma adecuada. Por tanto, otra de las aportaciones de la Tesis presentada es un seguidor de trayectorias 4D de UAS que puede corregir las desviaciones espaciales y temporales mientras sigue una trayectoria determinada. Actualmente, los autopilotos comerciales no ofrecen esta funcionalidad que permite mejorar la ocupación del espacio aéreo utilizando el tiempo como una dimensión adicional. Además, en esta Tesis se examina la capacidad de integración de módulos a bordo de detección y evitación de obstáculos, así como las consecuencias para los servicios de U-space. Se presenta un módulo capaz de detectar grandes obstáculos estáticos inesperados y capaz de generar una ruta alternativa para evitar dicho obstáculo. Por último, la arquitectura UTM presentada ha sido probada en entornos de desarrollo de simulación, pero también en escenarios reales con aeronaves no tripuladas. Estos escenarios se diseñaron seleccionando las aplicaciones de operación de UAS más relevantes, como la inspección de aerogeneradores, líneas eléctricas y agricultura de precisión, así como la monitorización de eventos y bosques. ATLAS y El Arenosillo fueron las sedes de las pruebas realizadas gracias a los proyectos europeos SAFEDRONE y GAUSS

Rule-based conflict management for unmanned traffic management scenarios

The growing use of Unmanned Aerial Vehicles (UAVs) operations will require effective conflict management to keep the shared airspace safe and avoid conflicts among airspace users. Conflicts pose high risk and hazard to human lives and assets as they ma may result in financial and human loss. The proposed rule-based conflict management model consists of three main stages. The first stage includes strategic deconfliction during the flight plan generation. The second stage, pre-tactical deconfliction, applies a ground delay to the agent to resolve the conflict. The third stage corresponds to the tactical deconfliction, where the drone hovers or loiter in the last waypoint before the conflict area until the conflict time window passes. The proposed method differs from most existing conflict management approaches in that it applies deconfliction methods sequentially using a rule-based strategy. Furthermore, a high number of published studies do not consider realistic airspace constraints and potential airspace modernization concepts such as dynamic flight restrictions Assessment and validation are performed in three simulation scenarios that consider different patterns of the airspace availability in the areas where flights may be restricted, such as airfields, recreational areas, and prisons. The Particle Swarm Optimization (PSO) algorithm was used for drone path planning. For the simulated scenarios all of the conflicts were resolved after implementation of the proposed method. The implemented method is simple, flexible and suitable for the management of more complex and dense airspaces

Real-time trajectory optimisation models for next generation air traffic management systems

This paper presents models and algorithms for real-time 4-Dimensional Flight Trajectory (4DT) operations in next generation Communications, Navigation, Surveillance/Air Traffic Management (CNS/ATM) systems. In particular, the models are employed for multi-objective optimisation of 4DT intents in ground-based 4DT Planning, Negotiation and Validation (4-PNV) systems and in airborne Next Generation Flight Management Systems (NG-FMS). The assumed timeframe convention for offline and online air traffic operations is introduced and discussed. The adopted formulation of the multi-objective 4DT optimisation problem includes a number of environmental objectives and operational constraints. In particular, the paper describes a real-time multi-objective optimisation algorithm and the generalised expression of the cost function adopted for penalties associated with specific airspace volumes, accounting for weather models, condensation trails models and noise models

Development of Complexity Science and Technology Tools for NextGen Airspace Research and Applications

The objective of this research by NextGen AeroSciences, LLC is twofold: 1) to deliver an initial "toolbox" of algorithms, agent-based structures, and method descriptions for introducing trajectory agency as a methodology for simulating and analyzing airspace states, including bulk properties of large numbers of heterogeneous 4D aircraft trajectories in a test airspace -- while maintaining or increasing system safety; and 2) to use these tools in a test airspace to identify possible phase transition structure to predict when an airspace will approach the limits of its capacity. These 4D trajectories continuously replan their paths in the presence of noise and uncertainty while optimizing performance measures and performing conflict detection and resolution. In this approach, trajectories are represented as extended objects endowed with pseudopotential, maintaining time and fuel-efficient paths by bending just enough to accommodate separation while remaining inside of performance envelopes. This trajectory-centric approach differs from previous aircraft-centric distributed approaches to deconfliction. The results of this project are the following: 1) we delivered a toolbox of algorithms, agent-based structures and method descriptions as pseudocode; and 2) we corroborated the existence of phase transition structure in simulation with the addition of "early warning" detected prior to "full" airspace. This research suggests that airspace "fullness" can be anticipated and remedied before the airspace becomes unsafe

Enhancing Trajectory-Based Operations for UAVs through Hexagonal Grid Indexing: A Step towards 4D Integration of UTM and ATM

Aviation is expected to face a surge in the number of manned aircraft and drones in the coming years, making it necessary to integrate Unmanned Aircraft System Traffic Management (UTM) into Air Traffic Management (ATM) to ensure safe and efficient operations. This research proposes a novel hexagonal grid-based 4D trajectory representation framework for unmanned aerial vehicle (UAV) traffic management that overcomes the limitations of existing square/cubic trajectory representation methods. The proposed model employs a hierarchical indexing structure using hexagonal cells, enabling efficient ground based strategic conflict detection and conflict free 4D trajectory planning. Additionally, the use of Hexagonal Discrete Global Grid Systems provides a more accurate representation of UAV trajectories, improved sampling efficiency and higher angular resolution. The proposed approach can be used for predeparture conflict free 4D trajectory planning, reducing computational complexity and memory requirements while improving the accuracy of strategic trajectory conflict detection. The proposed framework can also be extended for air traffic flow management trajectory planning, Air Traffic Control (ATC) workload measurement, sector capacity estimation, dynamics airspace sectorization using hexagonal sectors and traffic density calculation, contributing to the development of an efficient UTM system, and facilitating the integration of UAVs into the national airspace system with AT