Civil Airspace Research Articles

Distributed Reactive Model Predictive Control for Collision Avoidance of Unmanned Aerial Vehicles in Civil Airspace

Safety in the operations of UAVs (Unmanned Aerial Vehicles) depends on the current and future reduction of technical barriers and on the improvements related to their autonomous capabilities. Since the early stages, aviation has been based on pilots and Air Traffic Controllers that take decisions to make aircraft follow their routes while avoiding collisions. RPA (Remotely Piloted Aircraft) can still involve pilots as they are UAVs controlled from ground, but need the definition of common rules, of a dedicated Traffic Controller and exit strategies in the case of lack of communication between the Ground Control Station and the aircraft. On the other hand, completely autonomous aircraft are currently banned from civil airspace, but researchers and engineers are spending great effort in developing methodologies and technologies to increase the reliability of fully autonomous flight in view of a safe and efficient integration of UAVs in the civil airspace. This paper deals with the design of a collision avoidance system based on a Distributed Model Predictive Controller (DMPC) for trajectory tracking, where anticollision constraints are defined in accordance with the Right of Way rules, as prescribed by the International Civil Aviation Organization (ICAO) for human piloted flights. To reduce the computational burden, the DMPC is formulated as a Mixed Integer Quadratic Programming optimization problem. Simulation results are shown to prove the effectiveness of the approach, also in the presence of a densely populated airspace.

Reachability-Based Forced Landing System

A major hurdle toward the integration of unmanned aerial systems into the civilian airspace is the development of a principled methodology for handling emergency landings. Most of the prior work in the area of emergency landings for unmanned aerial systems has been concerned with using computer vision to identify potential landing sites. However, reaching these sites may not be dynamically feasible, and the maneuver needed to reach these sites may not be obvious. In this paper, a reachability-based forced landing system is proposed that uses Hamilton–Jacobi–Bellman reachability to determine the feasible landing region of a distressed aircraft. The utility of this technique is displayed on a fixed-wing aircraft with engine failure. In addition, it is also shown how to synthesize a controller that guides the aircraft to any desired landing location inside the feasible landing region.

Network intrusion detection system for UAV ad-hoc communication: From methodology design to real test validation

The use of a swarm of low-cost, mission-specific drones to form a Flying Ad-hoc Network (FANET) has literally become a ’hotspot’ in the drone community. A number of studies have been conducted on how to achieve a FANET, but few have considered the security perspectives of this subject. FANET’s unique features have made it difficult to strengthen its defense against ever-changing security threats. Today, more and more FANET applications are implemented into civil airspace, but the development of FANET security has remained unsatisfactory. In this paper, we try to address this issue by proposing a new Intrusion Detection System (IDS), an hybrid method based on both spectral traffic analysis and a robust controller / observer for anomaly estimation inside UAV networks. The proposed hybrid method considers, as a preliminary step, a statistical signature of the traffic exchanged in the network. By examining the resulted signatures, the differences are used to select the accurate model for accurate estimation of that abnormal traffic. The proposed IDS design has been successfully applied to some relevant practical problems such as ad hoc networks for aerial vehicles, and the effectiveness is illustrated by using real traffic traces including Distributed Denial of Service (DDoS) attacks. Our first results show promising perspectives for Intrusion Detection System (IDS) in UAV communication networks. Indeed, different types of anomaly have been considered and they are all accurately detected by the intrusion detection process we propose in this paper. Finally, both simulation-based validation and real-time real-world based implementation of our IDS are described in this article.

Use of a Value Model to Ethically Govern Various Applications of Small UAS

Widespread use of small unmanned aircraft systems is becoming prominent in the US. From structural health monitoring to journalism, small unmanned aerial systems (sUAS) are allowing people to gain a view of their surroundings and conduct their jobs in ways like never before. With this come many ethical concerns that must be addressed before the sight of a sUAS flying overhead is a widely acceptable occurrence to a majority of the population. Currently, UAS operations used in civil airspace are governed by the Federal Aviation Administration (FAA) Part 107 rules, but these regulations do not address certain ethical considerations. This paper will use the concept of a value model to quantify these ethical concerns so that they may be encoded into the design of a UAS and evaluation of missions before the missions are conducted. This could prove valuable in addressing the ethical challenges that are faced when implementing unmanned aerial systems (UAS) operations into the airspace, especially when UASs are in airspace in densely populated areas.

Development of Small UAS Beyond-Visual-Line-of-Sight (BVLOS) Flight Operations: System Requirements and Procedures

Due to safety concerns of integrating small unmanned aircraft systems (UAS) into non-segregated airspace, aviation authorities have required a set of detect and avoid (DAA) systems to be equipped on small UAS for beyond-visual-line-of-sight (BVLOS) flight operations in civil airspace. However, the development of small UAS DAA systems also requires BVLOS flights for testing and validation. To mitigate operational risks for small UAS BVLOS flight operations, this paper proposes to initially test small UAS DAA systems in BVLOS flights in a restricted airspace with additional safety features. Later, this paper further discusses the operating procedures and emergency action plans for small UAS BVLOS flight operations. The testing results show that these safety systems developed can help improve operational safety for small UAS BVLOS flight operations.

Grey wolf optimization based sense and avoid algorithm in a Bayesian framework for multiple UAV path planning in an uncertain environment

Unmanned Air Vehicles (UAVs), which have been popular in the military context, have recently attracted attention of many researchers because of their potential civilian applications. However, before UAVs can fly in civilian airspace, they need to be able to navigate safely to their goal while maintaining separation with other manned and unmanned aircraft during the transit. Algorithms for autonomous navigation of UAVs require access to accurate information about the state of the environment in order to perform well. However, this information is often uncertain and dynamically changing. In this paper, a Grey Wolf Optimization (GWO) based algorithm is proposed to find the optimal UAV trajectory in presence of moving obstacles, referred to as Intruder Aircraft (IAs), with unknown trajectories. The solution uses an efficient Bayesian formalism with a notion of cell weighting based on Distance Based Value Function (DBVF). The assumption is that the UAV is equipped with the Automatic Dependent Surveillance-Broadcast (ADS-B) and is provided with the position of IAs either via the ADS-B or ground-based radar. However, future trajectories of the IAs are unknown to the UAV. The proposed method is verified using simulations performed on multiple scenarios. The results demonstrate the effectiveness of the proposed method in solving the trajectory planning problem of the UAVs.

Spectrum Management Issues for the Operation of Commercial Services with UAVs

Commercial operations for Unmanned Air Vehicles (a.k.a. Drones) are envisioned to allow new services over civilian airspace and neighborhoods such as package delivery, property inspections, and event photography among others. However, a communications infrastructure that supports the control and air traffic management interactions of these devices beyond line of sight operations is required. This infrastructure will rely on wireless communication links and their associated radio frequency spectrum resources for its implementation. This paper aims to present an analysis of current and upcoming spectrum policy issues that need to be taken into account and will affect UAV operations and their air traffic management in the near future. We also analyze how traditional cellular bands and equipment that were designed for terrestrial services might not be adequate for supporting UAV operations unless adequate spectrum management techniques are taken into account as a drone-based user terminal can be in range of several base stations at the same time and cause interference in a much wider area than that of a terminal in the ground. We provide a regulatory and technical context for discussions on whether commercial UAV operations can and should be supported by the use of spectrum resources managed and operated by commercial wireless service providers (LTE, 5G) or if assigning a specific frequency band for these operations would be better. We contrast the pros and cons of each approach under current and future expected technological advances related to spectrum management in order to provide a spectrum policy based view of how commercial UAV operations via small Unmmaned Air Systems (UAS) could take place in the near future with supporting technical information for their feasibility.

Development of Sense and Avoid system based on multi sensor integration for unmanned vehicle system

Unmanned Aerial Vehicles (UAV) have a great potential to replace manned aircraft in many tasks or missions. However, in order to allow these UAVs to execute their mission appropriately and especially to deploy them in national or civil airspace, UAVs must have a proper and reliable collision avoidance system. This avoidance system is known as a Sense and avoidance (SAA) system. The purpose of the system is to detect any obstacles either in static or moving condition and respond with proper avoidance maneuvers in order to maintain minimum separation distances. Therefore the research project deals with the development of a unique SAA system which is based on multisensory integration. In particular, it focuses on sensors, processing logic and hardware required on the UAVs to acquire situational awareness. Dissimilar kind of sensors which is optical and laser type is proposed to be employed, so that weaknesses from each individual sensor can be tolerated. Proper logics or algorithm related to the fusion of output from each sensor will also be studied.The combination of Extended KalmanFilter (EKF) and Differential Evolution(DE) method is used for the purpose of development of detection and tracking system which considered to be the main challenges in SAA system development. Subsequently, once the algorithms are put together, including maneuvers avoidance technique algorithm, the developed SAA system will be experimentally tested in order to validate and evaluate the overall capability of the system.

Taxonomy of Conflict Detection and Resolution Approaches for Unmanned Aerial Vehicle in an Integrated Airspace

This paper proposes a taxonomy of conflict detection and resolution (CD&R) approaches for operating unmanned aerial vehicles (UAVs) in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuvering, and autonomy. The factors are combined back selectively, with regard to their feasibility for operation in an integrated airspace, into several “generic approaches” that form the CD&R taxonomy. These generic approaches are then attributed to a number of available methods in the literature to determine their position in the overall CD&R scheme. The attribution shows that many proposed methods are actually unsuitable for operation in an integrated airspace. Furthermore, some part of the taxonomy does not have an adequate representative in the literature, suggesting the need to concentrate UAV CD&R research more in those particular parts. Finally, a multilayered CD&R architecture is built from the taxonomy, implementing the concept of defense in depth to ensure safe operation of UAVs in an integrated civil airspace.

Joseph covariance formula adaptation to Square-Root Sigma-Point Kalman filters

The development of a reliable Sense And Avoid (SAA) system is one of the limiting aspects for the integration into civil airspace of unmanned aerial vehicles, for which the market demand is becoming viral in many fields. To overcome these limitations, it is required that the SAA system perform equally or even better than the human eye. This can be achieved integrating information from different sensors using data fusion algorithms, like Bayesian estimators or neural network techniques. SAA system degradation could arise from both single sensor shortcomings and bad numerical behaviours, injected by the specific fusion algorithm, such as real machine round-off errors or divergences introduced by approximating strongly nonlinear functions. An alternative formulation of the Square-Root unscented Kalman filter (SRUKF) based on the Joseph form of the state covariance update step, is used in order to avoid numerical instabilities induced by ill-conditioned matrix problems. The novelty of this technique lies in the exploitation of the Sigma-Point Kalman filters, which ensure a higher-order accuracy in the nonlinear inference problem solving, and in the application of the Joseph update equation, which improves numerical robustness. Moreover, this approach prevents the algorithm from failing, avoiding the downdating process of the Cholesky factor when the SRUKF is used and to take advantage by the higher numerical stability assured by a lower matrix condition number.

Markov Decision Process-Based Distributed Conflict Resolution for Drone Air Traffic Management

Ensuring safety and providing timely conflict alerts to small unmanned aircraft, commonly known as drones, is important to their integration into civil airspace. This paper proposes a short-term conflict avoidance algorithm for an automated low-altitude, small unmanned aircraft traffic management system. The goal is to balance between aircraft safety and efficiency subject to uncertainty in the environment, aircraft, and pilot response. The proposed algorithm generates advisories for each aircraft to follow, and is based on decomposing a large multiagent Markov decision process and fusing their solutions. As a result, the method scales well and resolves conflicts efficiently. Further, this paper presents a massively distributed architecture used to implement the conflict avoidance algorithm on a practical scale in which simultaneous conflicts can be solved in parallel in tens of milliseconds. Our controller significantly outperforms two baseline algorithms based on uncoordinated and closest-threat heuristics. In terms of conflict probability, our simulations demonstrate that our method is an order of magnitude better than the latter and about 10% better than the former.

Filling the Regulatory Void for Launch and Reentry Safety Resulting from the Commercialization of Space Operations

ABSTRACT The commercial use of space is not a new concept. Satellites have provided commercial services since the 1960s. However, the launch and recovery of space vehicles was dominated by State operators or under State Contract until the end of the last century. While commercial launches continue to increase, the international regulatory frameworks related to launch and reentry are fundamentally unchanged and are not structured to support a competitive commercial launch industry. This paper examines the regulatory gaps in the existing frameworks, particularly in the international domain. While there remain unresolved questions with regard to ICAO as it applies to suborbital flight, the ability of ICAO to develop standards and recommended practices for the portion of the operation that takes place in civil airspace is clear. These standards are necessary to ensure the safety of civil airspace for both traditional airspace users and launch operators, and the interaction of spaceports with civil airspace.

Unmanned aircraft systems in the national airspace system

As the technological and operational capabilities of unmanned aircraft systems (UAS) have grown, so too have international efforts to integrate UAS into civil airspace. However, one of the major concerns that must be addressed in realizing this integration is that of safety. For example, UAS lack an on-board pilot to comply with the legal requirement that pilots see and avoid other aircraft. This requirement has motivated the development of a detect and avoid (DAA) capability for UAS that provides situational awareness and maneuver guidance to UAS operators to aid them in avoiding and remaining well clear of other aircraft in the airspace. The NASA Langley Research Center Formal Methods group has played a fundamental role in the development of this capability. This article gives a selected survey of the formal methods work conducted in support of the development of a DAA concept for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations.

The safe integration of military UAS in the (inter)national airspace: some underlying processes

This paper brings a social science perspective (from the ethnicity and diversity literature) to bear on a process that is regarded by many as essentially a technical one: the safe insertion of military unmanned aircraft systems (UAS) in the (inter)national European airspace. The aim of this qualitative study was to gain a more adequate scientific socio-technological understanding of the topic, so as to strengthen issue dialogue and discussion. Indeed, studying the "integration" of these UASs (as this process is often referred to) through the lens of acculturation literature revealed some socio-technological processes that have been little noticed but which seem to underlie and inform this debate. For example, some voices seem to be favoured over others, a well-known phenomenon in the ethnicity and diversity literature. Safety, it could even be argued, is in this debate the pivot point around which social and other dynamics revolve. Belief and power may thus be more important factors here--"masked" of course--than technical aspects of safety. The results of this study are important not only for the military since the incorporation of military UAS occurs, partially at least, in civilian airspace. Civil actors thus formed a substantial subset of those interviewed here.

The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace

The integration of drones into civil airspace is one of the most challenging problems for the automation of the controlled airspace, and the optimization of the drone route is a key step for this process. In this paper, we optimize the route planning of a drone mission that consists of departing from an airport, flying over a set of mission way points and coming back to the initial airport. We assume that during the mission a set of piloted aircraft flies in the same airspace and thus the cost of the drone route depends on the air traffic and on the avoidance maneuvers used to prevent possible conflicts. Two air traffic management techniques, i.e., routing and holding, are modeled in order to maintain a minimum separation between the drone and the piloted aircraft. The considered problem, called the Time Dependent Traveling Salesman Planning Problem in Controlled Airspace (TDTSPPCA), relates to the drone route planning phase and aims to minimize the total operational cost. Two heuristic algorithms are proposed for the solution of the problem. A mathematical formulation based on a particular version of the Time Dependent Traveling Salesman Problem, which allows holdings at mission way points, and a Branch and Cut algorithm are proposed for solving the TDTSPPCA to optimality. An additional formulation, based on a Travelling Salesman Problem variant that uses specific penalties to model the holding times, is proposed and a Cutting Plane algorithm is designed. Finally, computational experiments on real-world air traffic data from Milano Linate Terminal Maneuvering Area are reported to evaluate the performance of the proposed formulations and of the heuristic algorithms.

Comments: Technologies of the Future

Editor's column The future of technology in the global energy industry will be driven by cost pressures, the scope of government regulation, and increased digitization. DNV GL’s Technology Outlook 2025 report, released last month, lists six emerging technologies that it predicts will have a significant impact on the upstream sector over the next decade. While the technologies are not necessarily new to oil and gas, they are likely to be adopted at an accelerated pace and more broadly than currently. The report predicts these technologies will be increasingly in use over the next several years because of economic, regulatory, and environmental factors, and continued strong demand for hydrocarbons. The first technology, fully automated drilling operations, has the potential to improve the speed and safety of drilling operations and greatly reduce costs. But its widespread adoption will require a “complete redesign” of drilling processes in order to gain all of the benefits. It will also require the use of related technologies such as automated drillpipe handling, managed-pressure drilling, single-trip drilling, and better monitoring and diagnostic capabilities. Automated drilling could cut both drilling time and costs by up to 50% compared with conventional operations, the report says. Smart completions, including better monitoring and more precise control of production zones to maximize recovery, should be heavily adopted by the industry. “Low-cost smart completions,” reconfigured without a rig, could potentially boost additional output from complex reservoirs, such as thin oil pay zones. Subsea systems will rely more on monitoring and data analytics to enhance production stability. That will help better predict flow-related problems and ensure continuous flow from the well. Improved monitoring and analytics, with more sensors and higher computing power, will drive simpler field development through the use of longer tie-ins and simpler designs, said Pierre Sames, DNV GL’s group technology and research director. This will improve leak detection, inspection, maintenance, and repair, all contributing to uninterrupted flow and better integrity, he said. Rigless plugging and abandonment could be a particular boon in the North Sea, which has 8,000 wells that need attention. Current practice for plugging and abandonment involves costly permanent plugging, accounting for up to half of the total decommissioning expenses. Plugging without the use of a rig would require that plugging and abandonment be performed with the well tubing in place, according to the report. Autonomous inspection of pipelines and the use of biodegradable polymers for enhanced oil recovery also should be in full operation by 2025. Autonomous underwater vehicles are more efficient than remotely operated vehicles in performing regular pipeline inspection and will be equipped with sonars, cameras, and sensors. Unmanned aerial vehicles will be used for onshore pipelines, but regulations will need to clarify their further use in civil airspace. DNV GL forecasts the world to be consuming up to one-fifth more energy by 2025 than it does now. With operational cost pressures and oil price volatility, there will be a need to drill new wells more efficiently, highlighting the need for such technologies as fully automated drilling and smart completions, Sames said. JPT

Human Factors Guidelines for Unmanned Aircraft Systems

The pilot control stations of some unmanned aircraft systems (UASs) have been plagued by poor human–machine interfaces. Human factors guidelines focused on the unique challenges of unmanned aviation will be essential if UASs are to gain unrestricted access to civil airspace. We present a systematic approach that can assist in the development and organization of human factors guidelines for UAS pilot control stations and other human–machine interfaces.

The future of air traffic management: ATM master plan and SESAR

In this paper we analise the problems of the future development of the system flow management of air traffic with basic aim of overcoming these disadvantages of existing air traffic management system. During the last century Europe did not have, unlike the United States, a joint civilian airspace. European airspace is among the busiest in the world, with over 33,000 flights a day, while the spatial concentration of airports in Europe is very high. These factors make the work of air traffic control in Europe very complex. The existing model of organization of airspace, that is. fragmentation and inefficiency of European air traffic control could not respond to the new needs of air traffic in terms of reducing delays, reducing the price of services, increasing safety and reducing impact on environment. European airlines have expressed in early XXI century the need to accelerate the modernization of air traffic control to maximize efficiency. Single European Sky Air Traffic Management Research Programme (SESAR) brought the innovations that strongly increased efficiency and reduced costs in air transport in Europe. Also, in June 2010, the European and US authorities have reached a preliminary agreement on interoperability between their future systems for air traffic management-SESAR and NextGen (Next Generation Air Transportation System), in order to overcome the fragmentation and inefficiency of the system for air traffic management, reduce delays and achieve significant savings in fuel.

Estimated levels of safety for small unmanned aerial vehicles and risk mitigation strategies

In this paper the risks posed by small unmanned aerial vehicles (UAV) 1 are determined using quantitative methods, to calculate the estimated level of safety (ELS). The aim is to determine if the use of small UAVs for typical low altitude long endurance missions creates any increased risk versus manned aviation accident rates. The risk discussion includes both perceived concerns with the small UAV and the real physical risks posed. Once the ELS is known, possible mitigation methods are presented that may improve the safety of the small UAV to a level where it may considered as having an equivalent level of safety as manned aircraft operating in the same unsegregated civilian airspace.

An Automated Emergency Landing System for Fixed‐Wing Aircraft: Planning and Control

A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure, and aircraft. To date, few field‐demonstrated systems have been presented that show online replanning and repeatability from failure to touchdown. This paper presents the development of the guidance, navigation, and control (GNC) component of an automated emergency landing system (AELS) intended to address this gap, suited to a variety of fixed‐wing aircraft. Field‐tested on both a fixed‐wing unmanned aerial vehicle (UAV) and Cessna 172R during repeated emergency landing experiments, a trochoid‐based path planner computes feasible trajectories, and a simplified control system executes the required maneuvers to guide the aircraft toward touchdown on a predefined landing site. This is achieved in zero‐thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial, and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and replans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field‐tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases.