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The safe integration of a large number of unmanned aircraft systems (UASs) into the National Airspace System (NAS) is essential for advanced air mobility. This requires reliable air-to-air transmission systems and robust collision avoidance algorithms. Automatic Dependent Surveillance-Broadcast (ADS-B) is a potential solution for a dependable air-to-air messaging system, but its reliability when stressed with hundreds to thousands of vehicles operating simultaneously is in question. This paper presents an ADS-B model and analyzes the capabilities of the Universal Access Transceiver (UAT), which operates at a frequency of 978 MHz. We use a probabilistic collision avoidance algorithm to examine the impact of varying parameters, including the number of vehicles and the transmission power of the UAT, on the overall safety of the vehicles. Additionally, we investigate the root causes of co-channel interference, proposing enhancements for safe operations in environments with a high density of UAS. Simulation results show message success and collision rates. With our proposed enhancements, UAT ADS-B can provide a decentralized air traffic system that operates safely in high-density situations.

The subject of autonomy within unmanned aerial vehicles (UAVs) has proven to be a remarkable research field – mostly due to the development of AI techniques within embedded advanced bespoke microcontrollers – during the last several decades. For drones, as safety-critical systems, there is an increasing need for onboard detect & avoid (DAA) technology i) to see, sense or detect conflicting traffic or imminent non-cooperative threats due to their high mobility with multiple degrees of freedom and the complexity of deployed unstructured environments, and subsequently ii) to take the appropriate actions to avoid collisions depending upon the level of autonomy. The safe and efficient integration of UAV traffic management (UTM) systems with air traffic management (ATM) systems, using intelligent autonomous approaches, is an emerging requirement where the number of diverse UAV applications is increasing on a large scale in dense air traffic environments for completing swarms of multiple complex missions flexibly and simultaneously. Significant progress over the past few years has been made in detecting UAVs present in aerospace, identifying them, and determining their existing flight path. This study makes greater use of electronic conspicuity (EC) information made available by PilotAware Ltd (https://www.pilotaware.com) in developing an advanced collision management methodology – Drone Aware Collision Management (DACM) – capable of determining and executing a variety of time-optimal evasive collision avoidance (CA) manoeuvres using a reactive geometric conflict detection and resolution (CDR) technique. The merits of the DACM methodology have been demonstrated through extensive simulations and real-world field tests in avoiding mid-air collisions (MAC) between UAVs and manned aeroplanes. The results show that the proposed methodology can be employed successfully in avoiding collisions while limiting the deviation from the original trajectory in highly dynamic aerospace without requiring sophisticated sensors and prior training. With the proposed technological improvement equipped with Artificial Intelligence (AI) techniques, MAC risks which cannot be avoided with the current off-the-shelf sensor technologies, in particular, between flights with very high velocities, can be definitely prevented with the accurate measurements and state and situation awareness (SSA) that uses a global coverage strategy with real-time low latency EC data feeds acquired from all aircraft. The MAC standards, dictated by the aviation authorities, can be mandated for UAVs considering the reliable decision-making abilities of DACM – without creating new collision risks during evasive manoeuvres, which can expedite the safe and efficient integration of UAVs into ATM systems.

This paper provides an analytical framework to address the definition of sensing requirements in non-cooperative UAS sense and avoid. The generality of the approach makes it useful for the exploration of sensor design and selection trade-offs, for the definition of tailored and adaptive sensing strategies, and for the evaluation of the potential of given sensing architectures, also concerning their interface to airspace rules and traffic characteristics. The framework comprises a set of analytical relations covering the following technical aspects: field of view and surveillance rate requirements in azimuth and elevation; the link between sensing accuracy and closest point of approach estimates, expressed though approximated derivatives valid in near-collision conditions; the diverse (but interconnected) effects of sensing accuracy and detection range on the probabilities of missed and false conflict detections. A key idea consists of focusing on a specific target time to closest point of approach at obstacle declaration as the key driver for sensing system design and tuning, which allows accounting for the variability of conflict conditions within the aircraft field of regard. Numerical analyses complement the analytical developments to demonstrate their statistical consistency and to show quantitative examples of the variation of sensing performance as a function of the conflict geometry, as well as highlighting potential implications of the derived concepts. The developed framework can potentially be used to support holistic approaches and evaluations in different scenarios, including the very low-altitude urban airspace.

Performance requirements for detect, alert, and avoid (DAA) systems for remotely piloted aircraft systems (RPAS) are under development by many regulatory agencies and standards bodies. A DAA system can be decomposed into three functions, “detect” — situational awareness; “alert” — determination of traffic that may be in conflict, evaluation of the de-conflicting flight path, and informing the pilot-in-command; and “avoid” — avoidance maneuver execution, and determination of “clear of conflict”. The “Detect” function of a DAA system depends on the sensor, target, and environment characteristics (e.g., signal-to-noise ratio of the target vs. background). The “alert” function depends on conflict prediction algorithms and human factors requirements. The “avoid” function depends on the RPAS maneuvering performance, airspace “rules”, and the size of the protection volume. The aforementioned factors impact the time required to calculate, and execute, an avoidance maneuver that will guarantee a prescribed miss distance, and dominate the “detect” requirements of a sensor. This paper describes DAAMSim: a publicly available modeling and simulation framework, developed by the National Research Council of Canada, to support the determination of DAA system requirements, and evaluation of DAA system performance. The framework described herein incorporates the functional components including various sensor, tracker, and avoid models; data replay; visualization tools; and offline metrics. Further, this paper presents sample results of the framework’s ability to determine DAA system requirements for various degrees of RPAS and intruder performance, and concludes with a description of future work activities.

Air traffic safety is the primary concern when it comes to the integration of Unmanned Aircraft Systems in the civil airspace. At the tactical level, the goal is to quantify en-route safety through pairwise separation minima. Unmanned Aircraft Systems make use of Detect and Avoid systems to remain, or regain well clear from other aircraft. There is already a well clear definition adopted for large Unmanned Aircraft Systems, however, this definition is not adequate and applicable to small Unmanned Aircraft Systems operating in low altitudes. In order to ensure the safe separation of various types of sUAS with different performances, a self-separation method is proposed. The method is based on dynamic protection zone, an early concept developed by US Air Force and later adapted into a time-based Detect and Avoid self-separation method. This paper outlines an engineering approach on designing a generic methodology, to define well clear among small Unmanned Aircraft Systems. For this purpose, both unmanned aircraft and systems performance are considered. Furthermore, we specify and recommend appropriate well clear thresholds and Detect and Avoid alerting times, based on the results the severity of loss of well clear. Several influencing factors such encounter geometry, speed and uncertainties in Communication, Navigation and Surveillance systems are examined to obtain efficient separation criteria.

The full integration of Remotely Piloted unmanned vehicles into civil airspace requires first and foremost the integration of a traffic Detect and Avoid (DAA) system into the vehicle. The DAA system supports remote pilots in performing their task of remaining Well Clear from other aircraft and avoiding collisions. Several studies related to the design of a Remain Well Clear function have been performed that served as input for the development of technical standards applicable to non-European countries. In this paper, a Remain Well Clear implementation is proposed that, using the results of past international projects, fits European airspace needs and specificities and can be acceptable to both remote pilots and air traffic controllers, with only minimal impact on the standard operating procedures used for manned aircraft. The proposed Remain Well Clear software has been successfully validated through real-time simulations with pilots and controllers in the loop considering traffic encounters and mission scenarios typically found in European airspace. The achieved results highlight the appropriate situational awareness provided by the proposed RWC function and its effective support to the remote pilot in making adequate decisions in conflict solving. Real-time simulation tests showed that, in almost all cases, an RWC maneuver is successfully performed, giving the RP sufficient time to assess the conflict, coordinate with the controller, if needed, and execute the maneuver. The fundamental role of the proposed RWC function has been especially evident in uncontrolled airspace classes where the controller does not provide any separation provision. Moreover, its effectiveness has also been tested in encounters with aircraft flying under visual flight rules in controlled airspace, where the controller is not informed or has less information regarding these aircraft. The results from validation tests imply two key potential safety benefits, namely: the mitigation of performing a collision avoidance maneuver and the prevention of potential conflict while not disrupting the traffic flow with possible further consequences of generating other potentially hazardous situations. [ABSTRACT FROM AUTHOR]

Services that exploit Unmanned Aircraft Systems (UAS) are poised to revolutionise the service industry with a projected value of 71 BUSD by the end of the decade. A key enabler of this technology is the unlocking of autonomous Beyond Visual Line of Sight (BVLOS) operations. BVLOS operations will depend on a robust Detect and Avoid (D&A) capability. Yet, currently in the UK and EU, BVLOS operations are only allowed in specific cases and scenarios. As a result, the technological landscape for the development of robust D&A faces limitations, and there is little market incentive for development. Furthermore, while automated BVLOS is a future technology, a strong D&A capability is of importance now for all types of UAS operations. As the remote pilot has to deal with information overload from the controller device and the environment. These high-risk UAS operations are becoming more common. In this paper, we discuss the current legal framework in the UK making comparisons to EU countries. We make the case that even when an operation abides by the current framework the remote pilot is exposed to several legal liabilities. We review the roadmaps for UAS adoption (including certification processes for UAS-based products) and highlight that for software-intensive systems, key steps are missing to assure the quality of the product. Finally, we build on these findings to set forwards a path to complement future certification processes to enable autonomous based UAS operations to share the airspace with remotely piloted operations. [ABSTRACT FROM AUTHOR]

Specific Operations Risk Assessment (SORA) is a methodology developed by the Joint Authority on Rulemaking for Unmanned Systems (JARUS) for safely conducting and evaluating Remotely Piloted Aircraft Systems (RPAS) operations in specific airspace. Many regulators, including Transport Canada (TC), the civilian aviation authority in Canada, have adopted the SORA approach to guide RPAS operators in their applications for Beyond Visual Line of Sight (BVLOS) flight. Although the qualitative approach on how to assess the performance of a Detect and Avoid (DAA) system is outlined in the SORA, a quantitative and agreed-upon approach, on how to ensure that the specific DAA system meets the required Risk Ratio criteria, has yet to be established. This paper proposes a practical approach to determining the Risk Ratio, considering sensor performance, RPA maneuvering characteristics, and airspace specifics. The developed approach relies on publicly available modelling frameworks and airspace models. Illustrative examples of applying the method to determine the Risk Ratio of specific DAA systems are presented in the paper along with a discussion on the challenges of implementing SORA into BVLOS regulations for RPAS.

The full integration of Remotely Piloted unmanned vehicles into civil airspace requires first and foremost the integration of a traffic Detect and Avoid (DAA) system into the vehicle. The DAA system supports remote pilots in performing their task of remaining Well Clear from other aircraft and avoiding collisions. Several studies related to the design of a Remain Well Clear function have been performed that served as input for the development of technical standards applicable to non-European countries. In this paper, a Remain Well Clear implementation is proposed that, using the results of past international projects, fits European airspace needs and specificities and can be acceptable to both remote pilots and air traffic controllers, with only minimal impact on the standard operating procedures used for manned aircraft. The proposed Remain Well Clear software has been successfully validated through real-time simulations with pilots and controllers in the loop considering traffic encounters and mission scenarios typically found in European airspace. The achieved results highlight the appropriate situational awareness provided by the proposed RWC function and its effective support to the remote pilot in making adequate decisions in conflict solving. Real-time simulation tests showed that, in almost all cases, an RWC maneuver is successfully performed, giving the RP sufficient time to assess the conflict, coordinate with the controller, if needed, and execute the maneuver. The fundamental role of the proposed RWC function has been especially evident in uncontrolled airspace classes where the controller does not provide any separation provision. Moreover, its effectiveness has also been tested in encounters with aircraft flying under visual flight rules in controlled airspace, where the controller is not informed or has less information regarding these aircraft. The results from validation tests imply two key potential safety benefits, namely: the mitigation of performing a collision avoidance maneuver and the prevention of potential conflict while not disrupting the traffic flow with possible further consequences of generating other potentially hazardous situations.

In this work, a Detect and Avoid system is presented for the autonomous navigation of Unmanned Aerial Vehicles (UAVs) in Urban Air Mobility (UAM) applications. The current implementation is designed for the operation of multirotor UAVs in UAM corridors. During the operations, unauthorized flying objects may penetrate the corridor airspace posing a risk to the aircraft. In this article, the feasibility of using a solid-state LiDAR (Light Detecting and Ranging) sensor for detecting and positioning these objects was evaluated. For that purpose, a commercial model was simulated using the specifications of the manufacturer along with empirical measurements to determine the scanning pattern of the device. With the point clouds generated by the sensor, the system detects the presence of intruders and estimates their motion to finally compute avoidance trajectories using a Second Order Cone Program (SOCP) in real time. The method was tested in different scenarios, offering robust results. Execution times were of the order of 50 milliseconds, allowing the implementation in real time on modern onboard computers.

This study elaborates the conflict management framework of unmanned aerial vehicles, focusing on the identification of the spatiotemporal interdependencies between them, with consideration of the future scalability problems in highly dense traffic scenarios. The paper first tries to justify the applied separation criteria among small cooperative unmanned aerial vehicles based on their performance characteristics and the planned missions' type. The adopted criteria, obtained from the simulations of 160 missions, present a testing asset, referring to a current lack of the spatiotemporal requirements and a need for extending the research in this area to provide a more rapid integration of these vehicles into the civil controlled airspace. The paper then elaborates the computational framework for the conflict detection and resolution function and operational metrics for causal identification of the spatiotemporal interdependencies between two or more cooperative vehicles. The vehicles are considered as a conflict mission system that strives to achieve an efficient solution by applying certain maneuvering measures, before a loss of separation occurs. The operational trials of five local, short-range missions, supported by the simulation scenario, demonstrate the potential for a time-based complexity analysis in the conflict resolution processes with less demanding and more efficient coordinated maneuvers. The results show that those maneuvers would not induce any new conflicts and disrupt the cooperative mission system when the spatial capacity only might not be favorable in provision of the avoidance maneuvers within an available airspace. [ABSTRACT FROM AUTHOR]

A safe integration of drones into the airspace is fundamental to unblock the potential of drone applications. U-space is the drone traffic management solution for Europe, intended to handle a large number of drones in the airspace, especially at very low level (VLL). This paper presents the procedures we have designed and tested in real flights in the SAFEDRONE European project to pave the way for a safe integration of drones into the airspace using U-space services. We include three important aspects: Design of procedures related to no-fly zones, ensure separation with manned aircraft, and autonomous non-cooperative detect-and-avoid (DAA) technologies. A specific U-space architecture has been designed and implemented for flight campaigns with up to eight drones with different configurations and a manned aircraft. From this experience, specific recommendations about procedures to exit and avoiding no-fly zones are presented. Additionally, it has been concluded that the use of surveillance information of manned aircraft will allow a more efficient use of the airspace while maintaining a proper safety level, avoiding the creation of large geofence areas.

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.

Vision-based aircraft detection technology may provide a credible sensing option for automated detect and avoid in small-to-medium size fixed-wing unmanned aircraft systems (UAS). Reliable vision-based aircraft detection has previously been demonstrated in sky-region sensing environments. This paper describes a novel vision-based system for detecting aircraft below the horizon in the presence of ground clutter. We examine the performance of our system on a data set of 63 near collision encounters we collected between a camera-equipped manned aircraft and a below-horizon target. In these 63 encounters, our system successfully detects all aircraft, at an average detection range of 1890 m (with a standard error of 43 m and no false alarms in 1.1 h). Furthermore, our system does not require access to inertial sensor data (which significantly reduces system cost) and operates at over 12 frames per second. [ABSTRACT FROM AUTHOR]

Detect and Avoid (DAA) systems are complex communication and locational technologies comprising multiple independent components. DAA technologies support communications between ground-based and space-based operations with aircraft. Both manned and unmanned aircraft systems (UAS) rely on DAA communication and location technologies for safe flight operations. We examined the occurrence and duration of communication losses between radar and automatic dependent surveillance-broadcast (ADS-B) systems with aircraft operating in proximate airspace using data collected during actual flight operations. Our objectives were to identify the number and duration of communication losses for both radar and ADS-B systems that occurred within a discrete time period. We also investigated whether other unique communication behavior and anomalies were occurring, such as reported elevation deviations. We found that loss of communication with both radar and ADS-B systems does occur, with variation in the length of communication losses. We also discovered that other unexpected behaviors were occurring with communications. Although our data were gathered from manned aircraft, there are also implications for UAS that are operating within active airspaces. We are unaware of any previously published work on occurrence and duration of communication losses between radar and ADS-B systems. [ABSTRACT FROM AUTHOR]

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.