UAS Traffic Management Research Articles

SAFETY ANALYSIS OF GOODS TRANSPORTATION BY UNMANNED AERIAL VEHICLES

Modern transport companies around the world actively study the possibility of intra-urban transportation of goods using unmanned aerial vehicles (UAV).The objective of the study is to reveal the existing problems preventing full-scale introducing of UAVs into the operations of logistics centers that accomplish cargo delivery in modern megacities as well as to propose a possible option for their solution.The study conducted applying the methods of comparative analysis and generalization showed that the main obstacle to the use of unmanned aerial vehicles for cargo delivery is currently unsettled problem of safety when UAVs operate in the urban environment.The study has analyzed the worldwide UAV traffic safety management programs. Among the programs reviewed were U-Space (the program is implemented by the European Commission and other participants); NASA Unmanned Aircraft System Traffic Management (the program is implemented by NASA and the US Federal Aviation Administration); European Aviation Safety Agency drone categories (the program is implemented by European Aviation Safety Agency (EASA)); Urban Traffic Management of Unmanned Aircraft System (the program is implemented by Air Traffic Management Research Institute (ATMRI) and other participants). The analysis showed that these programs paid a lot of attention to preventing the UAVs collisions with other air vehicles. But almost no attention was paid to the fact that the flight routes of unmanned aerial vehicles would intersect with the ground highways.The analysis carried out in the article allows us to conclude that one of the solutions to the problem of UAV implementation in the field of cargo delivery is the development of a new concept of UAV traffic safety in the urban conditions, which will take into account the threat of collision of cargo UAV not only with air vehicles but also with ground ones. The concept should determine the requirements for thetechnology for safe traffic of drones over the main surface transport routes including highways, highspeed railways, etc. The development of such a concept will be a turning point for starting the fullscale use of UAVs as a new and effective means of cargo delivery in the city, which, in its turn, willcreate the next-generation transport infrastructure in the cities.

System Operation of Regional UTM in Taiwan

The hierarchical unmanned aerial systems (UAS) traffic management (UTM) is proposed for UAS operation in Taiwan. The proposed UTM is constructed using the similar concept of ATM from the transport category aviation system. Based on the airspace being divided by 400 feet of altitude, the RUTM (regional UTM) is managed by the local government and the NUTM (national UTM) by the Civil Aeronautical Administration (CAA). Under construction of the UTM system infrastructure, this trial tests examine the effectiveness of UAV surveillance under 400 feet using automatic dependent surveillance-broadcast (ADS-B)-like on-board units (OBU). The ground transceiver station (GTS) is designed with the adoptable systems. In these implementation tests, five long-range wide area network (LoRa) gateways and one automatic packet reporting system (APRS) I-Gate are deployed to cover the Tainan Metropolitan area. The data rates are set in different systems from 8 to 12 s to prevent from data conflict or congestion. The signal coverage, time delay, data distribution, and data variance in communication are recorded and analyzed for RUTM operation. Data streaming and Internet manipulation are verified with cloud system stability and availability. Simple operational procedures are defined with priority for detect and avoid (DAA) for unmanned aerial vehicles (UAVs). Mobile communication and Zello broadcasts are introduced and applied to establish controller-to-pilot communication (CPC) for DAA. The UAV flight tests are generally beyond visual line-of-sight (BVLOS) near suburban areas with flight distances to 8 km. On the GTS deployment, six test locations examine communication coverage and effectiveness using ADS-B like OBUs. In system verification, the proposed ADS-B like OBU works well in the UTM infrastructure. The system feasibility is proven with support of receiving data analysis and transceiver efficiency. The trial test supports RUTM in Taiwan for UAV operations.

Influencing factors of low-altitude unmanned aircraft navigation using AHP

This study examines whether unmanned aircraft systems (UAS) operated in the context of UAS traffic management (UTM) can be properly operated in its flight environment. In detail, this study examines the influencing navigation factors affecting UASs during flight and examines factors affecting the navigation of UASs under UTM. After deriving various factors affecting navigation, their importance are determined by applying the analytic hierarchy process technique, and the important influencing factors are examined. For low-altitude UAS navigation, errors are classified into navigation-system and flight-technical errors, and a hierarchy is constructed for their sub-factors affecting the influencers. Through this, influencing factors for precise navigation of low-altitude UAS are analyzed, and high importance items are identified

Scalable Distributed State Estimation in UTM Context.

This article proposes a novel approach to the Distributed State Estimation (DSE) problem for a set of co-operating UAVs equipped with heterogeneous on board sensors capable of exploiting certain characteristics typical of the UAS Traffic Management (UTM) context, such as high traffic density and the presence of limited range, Vehicle-to-Vehicle communication devices. The proposed algorithm is based on a scalable decentralized Kalman Filter derived from the Internodal Transformation Theory enhanced on the basis of the Consensus Theory. The general benefit of the proposed algorithm consists of, on the one hand, reducing the estimation problem to smaller local sub-problems, through a self-organization process of the local estimating nodes in response to the time varying communication topology; and on the other hand, of exploiting measures carried out nearby in order to improve the accuracy of the local estimates. In the UTM context, this enables each vehicle to estimate both its own position and velocity, as well as those of the neighboring vehicles, using both on board measurements and information transmitted by neighboring vehicles. A numerical simulation in a simplified UTM scenario is presented, in order to illustrate the salient aspects of the proposed algorithm.

Advances in intelligent and autonomous navigation systems for small UAS

A significant growth in Unmanned Aircraft System (UAS) operations has been observed over the past decade, largely driven by the emergence of new commercial opportunities and use-cases. This has posed new technological and regulatory challenges in order to address the complex safety, efficiency and sustainability requirements associated with UAS operations in an increasingly congested airspace. The growing need for trusted autonomy in UAS operations imposes demanding performance requirements on Navigation and Guidance Systems (NGS), both in terms of accuracy, integrity, continuity and availability. In most current NGS implementations, system autonomy is tightly constrained within a specified set of operational and environmental conditions through a large number of explicit rules. Recent breakthroughs in Artificial Intelligence (AI)-based methods and the emergence of highly-parallelized processor boards with low form-factor has led to the opportunity to employ Machine Learning (ML) techniques to enhance navigation system performance, particularly for small UAS (sUAS), which account for the majority of current and future unmanned aircraft use-cases. sUAS navigation systems typically employ diverse low Size, Weight, Power and Cost (SWaP-C) sensors such as Global Navigation Satellite System (GNSS) receivers, MEMS-IMUs, magnetometers, cameras and Lidars for localization, obstacle detection and avoidance. This paper presents a comprehensive review of conventional sUAS navigation systems, including aspects such as system architecture, sensing modalities and data-fusion algorithms. Additionally, performance monitoring and augmentation strategies are critically reviewed and assessed against current and future UAS Traffic Management (UTM) requirements. The primary focus is on the identification of key gaps in the literature where the use of AI-based methods can potentially enhance navigation performance. A critical review of AI-based methods and their application to sUAS navigation is conducted, along with an assessment of the performance benefits they provide over conventional navigation systems. Reviewed methods include but are not restricted to Artificial Neural Networks (ANN) such as Convolutional and Recurrent Neural Networks (CNN and RNN), Support Vector Machines (SVM) and ensemble techniques. The key challenges associated with adapting these methods to address sUAS operational objectives are clearly identified. The review also covers the assurance of predictable, deterministic system behaviour which is a key requirement to support system certification. The review and analysis will inform the reader of the applicability of various AI/ML methods to sUAS navigation and autonomous system integrity monitoring, and its likely role in the ongoing UTM evolution.

Development of Hierarchical UAS Traffic Management (UTM) in Taiwan

The unmanned aerial vehicles (UAVs) will soon be legally flying into airspace in Taiwan and many countries. UAS traffic management (UTM) becomes an important issue to challenge aviation safety. A hierarchical UTM is proposed and constructed based on the concept of Air Traffic Management (ATM) for the manned aviation system. The proposed Regional UTM (RUTM) and National UTM (NUTM) are hierarchical infrastructure to offers traffic management services for all legal UAV flights in Taipei Flight Information Region (TPE FIR) under and over 400 feet. The proposed UTM provides UAV/pilot log-in/out, flight planning, geo-fencing, detect and avoid (DAA), logbook records, big data analysis, ground control redundant support and controller-pilot communication on multi-window monitor system. UTM data are encrypted to prevent hijacking threat to low altitude UAVs. The UTM adopts ADS-B Like communication infrastructure to offer affordable cost for all UAVs with high reliable surveillance data reporting. The ADS-B Like surveillance mechanism includes 4G/LTE, LoRa, APRS and XBee. Their gateway deployment is designed and constructed with supports of Chung Hua Telecommunication (CHT) in urban and suburban areas. While those remote areas, such as mountain and deep forest, the National Forest Bureau workstation will be selected. The ADS-B Like communication will cover full airspace in Taiwan. Surveillance data reliability, continuity, integrity and availability will be examined by flight tests. The proposed Hierarchical UTM will launch trial runs in Tainan County of RUTM operation to verify the proposed concept, system performance and general operation into the national “UAS Innovative Experiment Project”.

Modern technological trends in the development of the ecosystem of cargo UAVs

Trends in the development of the ecosystem of cargo UAVs are considered. This ecosystem has appeared in the aviation industry, including civil unmanned aerial systems manufacturers and their components, software developers, integrators, UAV-based service providers, insurance companies and trading platforms. The architectural concept of unmanned aircraft system traffic management is discussed.

Intent Inference Based Trajectory Prediction and Smooth for UAS in Low-altitude Airspace with Geofence

In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System (UAS) in Unmanned Aircraft System Traffic Management (UTM), an Intent Based Trajectory Prediction and Smooth Based on Constrained State-dependent-transition Hybrid Estimation (CSDTHE-IBTPS) algorithm is proposed. Firstly, an intent inference method of UAS is constructed based on the information of ADS-B and geofence system. Moreover, a geofence layering algorithm is proposed. Secondly, the Flight Mode Change Points (FMCP) are used to define the relevant mode transition parameters and design the guard conditions, so as to generate the mode transition probability matrix and establish the continuous state-dependent-transition model. After that, the constrained Kalman filter (CKF) is applied to improve State-dependent-transition Hybrid Estimation (SDTHE) algorithm by applying equality constraint to the velocity of UAS in the straight phase and turning phase, respectively, and thus the constrained state-dependent-transition hybrid estimation (CSDTHE) algorithm is constructed. Finally, the results of intent inference and hybrid estimation are used to make trajectory prediction. Furthermore, each flight segment of trajectory is smoothed respectively by Rauch-Tung-Striebel (RTS) backward smooth method using the proposed CSDTHE-RTS algorithm, so as to obtain more accurate trajectory prediction results. The simulation shows that the proposed algorithm can reduce the errors of trajectory prediction and the time delay of intent inference.

Probabilistic Risk-Based Operational Safety Bound for Rotary-Wing Unmanned Aircraft Systems Traffic Management

A novel method to determine probabilistic operational safety bound for rotary-wing unmanned aircraft systems (UAS) traffic management is proposed in this paper. The key idea is to combine a deterministic model for rotary-wing UAS flying distance estimation to avoid conflict and a probabilistic uncertainty quantification methodology to evaluate the risk level (defined as the probability of failure) of separation loss between UAS. The proposed methodology results in a dynamic and probabilistic airspace reservation to ensure the safety and efficiency for future UAS operations. The model includes UAS performance, system updating frequency and accuracy, and weather conditions. Also, the parameterized probabilistic model includes various uncertainties from different sources and develops an anisotropic operational safety bound. Monte Carlo simulations are used to illustrate the operational safety bound determination with a specified risk level (i.e., probability of failure). It is known that uncertainty plays an important role in determining the operational safety bound size, and the proposed methodology provides a simple and efficient quantification of uncertainty impact on the safety bound with a prescribed risk level. It is also providing a useful tool to quantify uncertainty reduction with additional information and measurements in future UAS operations.

Physics-Based Freely Scalable Continuum Deformation for UAS Traffic Coordination

This article develops a novel physics-inspired traffic coordination approach and applies it to unmanned aircraft system (UAS) traffic management. We extend available physics-inspired approaches previously applied to 1-D traffic flow on highways and urban streets to support models of traffic coordination in higher dimension airspace for cases where no predefined paths exist. This article considers airspace as a finite control volume while UAS coordination, treated as continuum deformation, is controlled at the airspace boundaries. By partitioning airspace into planned and unplanned spaces, the article models nominal coordination in the planned airspace as the solution of a partial differential equation with spatiotemporal parameters. This article also improves resilience to vehicle failures with a resilient boundary control algorithm to update the geometry of the planned space when UAS problems threaten safe coordination in existing navigable airspace channels. To support UAS coordination at the microscopic level, we propose clustering vehicles based on vehicle performance limits. UAS clusters, with each UAS treated as a particle of a virtual rigid body, use leader–follower containment to acquire the macroscopic desired trajectory.

Usability Test of a Prototype Uas Awareness Interface for Public Users

A tool to give the public a window into Unmanned Aerial Systems (UAS) Traffic Management (UTM) operations was created from an existing data collection tool. The interface included a map and a table showing details about UAS operations that could be queried in a number of ways. Eleven participants attended the study, successfully completing a 19-item task set in about 30 minutes. They correctly found information for 87% of the non-subjective tasks at a rate of around a minute per task and rated the usability of the tool at the end of the session above the industry benchmark. Participants gave favorable reviews of the “public portal tool”, even reporting that they would be satisfied with less information than it presented. There were one or two elements of the display that users found distracting and some navigation functions that need improvement but, on balance, the public representatives liked the features they saw in, and had few criticisms of, the public portal tool. One important issue for the small Unmanned Aerial System community to resolve will be how much or how little information should be available about UTM operations to members of the public.

Unmanned Free Balloon Flight’s Integration into Unmanned Aircraft System Traffic Management

This paper describes and inspects unmanned aerial vehicle, unmanned aircraft system, unmanned aircraft system traffic management, light and medium unmanned free balloons. It presents future safety developments and goals of the European Union’s own airspace, but also the Hungarian free route airspace. The development and realization of Swiss U-Space is discussed. Hungarian flights statistics are analyzed. Based on statistics, realized and under development solutions there are recommendations in the paper for the integration of the flight tacking for the mentioned balloons. A real flight tracking test has been done and it is shown in this paper. Its properties are analyzed with conclusions for possible usage.

Probabilistic Risk Assessment and Mitigation for UAS Safety and Traffic Management

A probabilistic approach to help future UAS safety and traffic management is proposed. A probabilistic risk-based operational safety bound is first proposed. This will allow UAV to maintain the deviation from the trajectory plan within a ”buffer” zone, and keep away from obstacles. Uncertainty quantification, Monte Carlo simulation, and coordinate transformation techniques will be used. Additionally, an algorithm integrating reinforcement learning and the proposed operational safety bound will be developed which is used for collision avoidance and trajectory planning. This will provide a learning ability to UAVs in order to adapt their behavior to changing environments. Also, large-scale UAV management will be studied by using multi-agent generative adversarial imitation learning.

Traffic management for drones flying in the city

Air Traffic Management (ATM) is designed based on the notion of a pilot navigating an aircraft from within the aircraft. Increasing demand for Unmanned Aircraft Systems (UAS) usage and its safe integration into segregated/non-segregated airspace, on the other hand, have raised a question on the adoption of the current ATM for the UAS Traffic Management (UTM). The Procedures for Air Navigation Services-Air Traffic Management (PAN-ATM) and Procedures for Air Navigation Services - aircraft operations (PAN-OPS) rules are both developed for manned flight operations. Therefore, this work (i) defines the UTM system and describes its envisioned functionalities; (ii) performs an exploratory research to identify the distinctions between a manned and an unmanned flight operation and consequently the possible challenges to implement UTM with regard to the ATM; (iii) discusses potential Communication, Navigation and Surveillance (CNS) technologies to support the UTM system; and (iv) proposes an architectural framework for UTM based on the findings. It is important to highlight that this work is developed based on the assumption that the UAS will operate in the class G airspace (500 ft and below) in urban areas where the UAS are exposed to various obstacles such as static objects: high-rise buildings, trees, lamp posts, over-ground rail tracks and dynamic objects: cranes.

ESTABLISHING NEW FOUNDATIONS FOR THE USE OF REMOTELY-PILOTED AIRCRAFT SYSTEMS FOR CIVILIAN APPLICATIONS

Abstract. Skyopener is a project funded by the EU through the European GNSS Agency (GSA) in the framework of the Horizon 2020 program. Skyopener’s goal is contributing to the roadmap for the integration of civil Remotely Piloted Aircraft Systems (RPAS) into nonsegregated airspace, by providing and testing enabling technologies, in particular with reference to European initiative U-Space, aimed at establishing regulations and infrastructure for integration of unmanned aviation into shared airspace. The main outcomes of the project include: implementing and testing a reliable and secure redundant air-ground communication link, based on satellite and 3G/4G networks; integrating the mission management system and ground station with a UTM (Unmanned aerial system Traffic Management) client, and experimenting UTM services being deployed by one of the partners; demonstrating technical and economic feasibility of long- range missions beyond visual line of sight (BVLOS) by executing corridor mapping on a high-voltage powerline, and airport area surveys (e-TOD: electronic-Terrain Obstacle Database).

Improved Conflict Detection and Resolution for Service UAVs in Shared Airspace

In future unmanned aerial vehicle (UAV)-based services, UAV 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 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.

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.

Drónok piacához köthető üzleti felhasználási lehetőségek áttekin-tése a szegmens aktualitásainak tükrében

The objective of this article to give a clear and complete picture about the whole drone segment including the so called unmanned aircraft system traffic management market as well. It is still a living statement, that drone manufacturing and technology developments are far ahead of the current state of the national and international regulatory and standardization environment. The article presents the global drone market trends focusing on manufacturers and taking into account the most relevant, demanding stakeholders and the utilization possibilities of these tools on an international scale. Based on the available information the aim is to outline a domestic related forecast. The goal of HungaroControl Pte. Ltd. Co is to concentrate and work proactively within the segment taking into account the European and Hungarian interests to build an all-around UTM service for the drone community.

UAS Traffic Management (UTM) based on Flight Information Sharing and Coordination between Operators

UAS Traffic Management (UTM) based on Flight Information Sharing and Coordination between Operators

Flight Demonstration for Information Sharing to Avoid Collisions between Small Unmanned Aerial Systems (sUASs) and Manned Helicopters

This paper describes our work building and testing a concept to share information among operators of manned aircraft and small unmanned aerial systems (sUASs) using the same low-altitude airspace to reduce collision risk, which is an urgent issue due to the rapid growth of sUASs use in many countries. Our concept is to share the positions of manned aircraft and sUASs on a web-based UAS Traffic Management (UTM) platform and provide alerts that give the operators of sUAS sufficient time to land the sUASs before a manned aircraft reaches the designated minimum airspace distance necessary for separation from the sUASs. The purpose of this paper and the flight demonstrations is to investigate the feasibility and problems in building such a platform. This paper also reports on the latest sUAS situations, including regulatory discussions, operations, the experimental environment, and the required regulatory arrangements.