Improved conflict detection and resolution for service UAVs in shared airspace

In future UAV-based services, UAV (Unmanned Aerial Vehicle) fleets will be managed by several independent flight operation service providers in shared low-altitude airspace. Therefore, Conflict Detection and Resolution (CDR) methods that can solve conflicts---possible collisions between UAVs of different service providers---are a key element of the Unmanned Aircraft System Traffic Management (UTM) system. As our CDR method, we introduce an adaptation of ORCA, which is a state-of-the-art collision avoidance algorithm hitherto mainly used in a limited theoretical scope, to realistic UAV operations. Our approach, called Adapted ORCA, addresses practical considerations that are inherent to the deployment of UAVs in shared airspace, such as navigation inaccuracies, communication overhead, and flight phases. We validate our approach through simulations. First, by empirically tuning the ORCA parameters look-ahead time window and deconfliction distance, we are able to minimize the ORCA generated deviations from the nominal flight path. Second, by simulating realistic UAV traffic for delivery, we can determine a value for separation distance between UAVs that uses airspace efficiently

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations

Decentralized multi-agent path finding for UAV traffic management

The development of a real-world Unmanned Aircraft System (UAS) Traffic Management (UTM) system to ensure the safe integration of Unmanned Aerial Vehicles (UAVs) in low altitude airspace, has recently generated novel research challenges. A key problem is the development of Pre-Flight Conflict Detection and Resolution (CDR) methods that provide collision-free flight paths to all UAVs before their takeoff. Such problem can be represented as a Multi-Agent Path Finding (MAPF) problem. Currently, most MAPF methods assume that the UTM system is a centralized entity in charge of CDR. However, recent discussions on UTM suggest that such centralized control might not be practical or desirable. Therefore, we explore Pre-Flight CDR methods where independent UAS Service Providers (UASSPs) with their own interests, communicate with each other to resolve conflicts among their UAV operations--without centralized UTM directives. We propose a novel MAPF model that supports the decentralized resolution of conflicts, whereby different `agents', here UASSPs, manage their UAV operations. We present two approaches: (1) a prioritization approach and (2) a simple yet practical pairwise negotiation approach where UASSPs agents determine an agreement to solve conflicts between their UAV operations. We evaluate the performance of our proposed approaches with simulation scenarios based on a consultancy study of predicted UAV traffic for delivery services in Sendai, Japan, 2030. We demonstrate that our negotiation approach improves the ``fairness'' between UASSPs, i.e. the distribution of costs between UASSPs in terms of total delays and rejected operations due to replanning is more balanced when compared to the prioritization approach

Adaptive Airborne Separation to Enable UAM Autonomy in Mixed Airspace

The excitement and promise generated by Urban Air Mobility (UAM) concepts have inspired both new entrants and large aerospace companies throughout the world to invest hundreds of millions in research and development of air vehicles, both piloted and unpiloted, to fulfill these dreams. The management and separation of all these new aircraft have received much less attention, however, and even though NASAs lead is advancing some promising concepts for Unmanned Aircraft Systems (UAS) Traffic Management (UTM), most operations today are limited to line of sight with the vehicle, airspace reservation and geofencing of individual flights. Various schemes have been proposed to control this new traffic, some modeled after conventional air traffic control and some proposing fully automatic management, either from a ground-based entity or carried out on board among the vehicles themselves. Previous work has examined vehicle-based traffic management in the very low altitude airspace within a metroplex called UTM airspace in which piloted traffic is rare. A management scheme was proposed in that work that takes advantage of the homogeneous nature of the traffic operating in UTM airspace. This paper expands that concept to include a traffic management plan usable at all altitudes desired for electric Vertical Takeoff and Landing urban and short-distance, inter-city transportation. The interactions with piloted aircraft operating under both visual and instrument flight rules are analyzed, and the role of Air Traffic Control services in the postulated mixed traffic environment is covered. Separation values that adapt to each type of traffic encounter are proposed, and the relationship between required airborne surveillance range and closure speed is given. Finally, realistic scenarios are presented illustrating how this concept can reliably handle the density and traffic mix that fully implemented and successful UAM operations would entail

U.S. Unmanned Aerial Vehicles (UAVS) and Network Centric Warfare (NCW) impacts on combat aviation tactics from Gulf War I through 2007 Iraq

Unmanned, aerial vehicles (UAVs) are an increasingly important element of many modern militaries. Their success on battlefields in Afghanistan, Iraq, and around the globe has driven demand for a variety of types of unmanned vehicles. Their proven value consists in low risk and low cost, and their capabilities include persistent surveillance, tactical and combat reconnaissance, resilience, and dynamic re-tasking. This research evaluates past, current, and possible future operating environments for several UAV platforms to survey the changing dynamics of combat-aviation tactics and make recommendations regarding UAV employment scenarios to the Turkish military. While UAVs have already established their importance in military operations, ongoing evaluations of UAV operating environments, capabilities, technologies, concepts, and organizational issues inform the development of future systems. To what extent will UAV capabilities increasingly define tomorrow's missions, requirements, and results in surveillance and combat tactics? Integrating UAVs and concepts of operations (CONOPS) on future battlefields is an emergent science. Managing a transition from manned- to unmanned and remotely piloted aviation platforms involves new technological complexity and new aviation personnel roles, especially for combat pilots. Managing a UAV military transformation involves cultural change, which can be measured in decades.http://archive.org/details/usunmannedaerial109454211Turkish Air Force authors.Approved for public release; distribution is unlimited

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

Pre-flight conflict detection and resolution for UAV integration in shared airspace: Sendai 2030 model case

The increasing demand for services performed by Unmanned Aerial Vehicles (UAVs) requires the simulation of Unmanned Aircraft System Traffic Management (UTM) systems. In particular, Pre-Flight Conflict Detection and Resolution (CDR) methods need to scale to future demand levels and generate conflict-free paths for a potentially large number of UAVs before actual takeoff. However, few studies have examined realistic scenarios and the requirements for the UTM system. In this paper, we focus on the Sendai 2030 model case, a realistic projection of UAV usage for deliveries in one area in Japan. This model case considers up to 21,000 requests for Unmanned Aircraft Systems (UAS) operations over a 13 hour service time, and thus poses a challenge for the Pre-Flight CDR methods. Therefore, we propose an airspace reservation method based on 4DT (3D plus time Trajectories) and map the Pre-Flight CDR problem to a Multi-Agent Path Finding (MAPF) problem. We study first-come first-served (FCFS) and “batch” processing of UAS operation requests, and compare the throughput of those methods. We analyze the air traffic topology of deliveries by UAVs, and discuss several metrics to better understand the complexity of air traffic in the Sendai model case

System elements required to guarantee the reliability, availability and integrity of decision-making information in a complex airborne autonomous system

Current air traffic management systems are centred on piloted aircraft, in which all the main decisions are made by humans. In the world of autonomous vehicles, there will be a driving need for decisions to be made by the system rather than by humans due to the benefits of more automation such as reducing the likelihood of human error, handling more air traffic in national airspace safely, providing prior warnings of potential conflicts etc. The system will have to decide on courses of action that will have highly safety critical consequences. One way to ensure these decisions are robust is to guarantee that the information being used for the decision is valid and of very high integrity. [Continues.

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

Autonomous Collision avoidance for Unmanned aerial systems

Unmanned Aerial System (UAS) applications are growing day by day and this will lead Unmanned Aerial Vehicle (UAV) in the close future to share the same airspace of manned aircraft.This implies the need for UAS to define precise safety standards compatible with operations standards for manned aviation. Among these standards the need for a Sense And Avoid (S&A) system to support and, when necessary, sub¬stitute the pilot in the detection and avoidance of hazardous situations (e.g. midair collision, controlled flight into terrain, flight path obstacles, and clouds). This thesis presents the work come out in the development of a S&A system taking into account collision risks scenarios with multiple moving and fixed threats. The conflict prediction is based on a straight projection of the threats state in the future. The approximations introduced by this approach have the advantage of high update frequency (1 Hz) of the estimated conflict geometry. This solution allows the algorithm to capture the trajectory changes of the threat or ownship. The resolution manoeuvre evaluation is based on a optimisation approach considering step command applied to the heading and altitude autopilots. The optimisation problem takes into account the UAV performances and aims to keep a predefined minimum separation distance between UAV and threats during the resolution manouvre. The Human-Machine Interface (HMI) of this algorithm is then embedded in a partial Ground Control Station (GCS) mock-up with some original concepts for the indication of the flight condition parameters and the indication of the resolution manoeuvre constraints. Simulations of the S&A algorithm in different critical scenarios are moreover in-cluded to show the algorithm capabilities. Finally, methodology and results of the tests and interviews with pilots regarding the proposed GCS partial layout are covered