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This presentation to RTCA SC-228 WG1 shows preliminary results of closed-loop DAA simulations of low SWaP UA operations. Metrics to discuss include safety metrics and pilot workload.
Uncrewed aircraft system (UAS) observations from the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting (WRF) Model. The impact of assimilating targeted UAS observations in addition to surface observations was compared to that obtained when assimilating surface observations alone using observing system experiments (OSEs) for a terrain-driven flow case and a convection initiation (CI) case observed within Colorado’s San Luis Valley (SLV). The assimilation of UAS observations in addition to surface observations results in a clear increase in skill for both flow regimes over that obtained when assimilating surface observations alone. For the terrain-driven flow case, the UAS observations improved the representation of thermal stratification across the northern SLV, which produced stronger upvalley flow over the eastern half of the SLV that better matched the observations. For the CI case, the UAS observations improved the representation of the pre-convective environment by reducing dry biases across the SLV and over the surrounding terrain. This led to earlier CI and more organized convection over the foothills that spilled outflows into the SLV, ultimately helping to increase low-level convergence and CI there. In addition, the importance of UAS capturing an outflow that originated over the Sangre de Cristo Mountains and triggered CI is discussed. These outflows and subsequent CI were not well captured in the simulation that assimilated surface observations alone. We report that observations obtained with a fleet of UAS are shown to notably improve high-resolution analyses and short-term predictions of two very different mesogamma-scale weather events.
As the technological and operational capabilities of unmanned aircraft systems (UAS) continue to grow, so too does the need to introduce these systems into civil airspace. Unmanned Aircraft Systems Integration in the National Airspace System is a NASA research project that addresses the integration of civil UAS into non-segregated airspace operations. One of the major challenges of this integration is the lack of an onboard pilot to comply with the legal requirement that pilots see and avoid other aircraft. The need to provide an equivalent to this requirement for UAS has motivated the development of a detect and avoid (DAA) capability to provide the appropriate situational awareness and maneuver guidance in avoiding and remaining well clear of traffic aircraft. Formal methods has played a fundamental role in the development of this capability. This talk reports on the formal methods work conducted under NASA's Safe Autonomous System Operations project in support of the development of DAA 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 talk also discusses technical challenges in formal methods research in the context of the development and safety analysis of advanced air traffic management concepts.
As the volume of small unmanned aircraft systems (UAS) operations increases, the lack of weather products to support these operations becomes more problematic. One early solution to obtaining more information about weather conditions is to allow operators to share their observations and measurements with other airspace users. This is analogous to the AIREP and PIREP reporting systems in traditional aviation wherein pilots report weather phenomena they have observed or experienced to provide better situational awareness to other pilots. Given the automated nature of the small (under 55 lbs.) UAS platforms and operations, automated reporting of relevant information should also be supported. To promote automated exchange of these data, a well-defined data schema needs to be established along with the mechanisms for sending and retrieving the data. This paper examines this concept and offers an initial definition of the necessary elements to allow for immediate implementation and use.
There is an increasing need to fly UAS in the NAS to perform missions of vital importance to National Security and Defense, Emergency Management, and Science as well as commercial applications (e.g. cargo transport). To enable integration of UAS into the National Airspace System, several critical technical barriers must be eliminated, including: Separation Assurance/Sense and Avoid - the uncertainty surrounding the ability to interoperate in ATC environments and maintain safe separation from other aircraft in the absence of an on-board pilot. Human Systems Integration - lack of standards and guidelines with respect to UAS display information as well as lack of Ground Control Station (GCS) design requirements to operate in the NAS. Certification - lack of airworthiness requirements and safety-related data specific to the full range of UAS, or for their avionics systems or other components. Communications - lack of standard, certifiable data links and aviation safety spectrum to operate such links for civil UAS control communications.
Abstract Uncrewed aircraft system (UAS) observations collected during the 2018 Lower Atmospheric Process Studies at Elevation—a Remotely Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting Model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth, and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow were improved relative to that obtained both without data assimilation (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV, with reductions in both bias and the root-mean-square error of roughly 40% for each variable relative to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.
Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.
NASA RPAS Operational and Research Activities presentation discusses the UAS flight operations. UAS vehicles are discussed along with the missions they supported. This is a high level overview of UAS operations at NASA being presented to the RPAS (Remotely Piloted Aircraft Systems) Symposium.
This study evaluated the performance of four prototype unmanned aircraft detect-and-avoid (DAA) display configurations, each with different informational elements driven by alerting and guidance algorithms. Sixteen unmanned aircraft pilots flew each combination of the display configurations, with half being given zero DAA surveillance sensor uncertainty and the other half experiencing errors that were comparable, and in some cases slightly better than, errors that were measured in DAA system flight tests. The displays that showed intruder alert information in altitude and heading bands had significantly fewer losses of well clear compared with alternative displays that lacked that information. This difference was significant from a statistical and practical perspective: those losses that did occur lasted for shorter periods and did not penetrate as far into the geometric "separation cylinder" as those in the non-banded displays. A modest level of DAA surveillance sensor uncertainty did not affect the proportion of losses of well clear or their severity. It is recommended that DAA traffic displays implement a band-type display in order to improve the safety of UAS operations in the National Airspace System. Finally, this report provides pilot response time distributions for responding to DAA alerts.
The UAS-NAS Project demo will showcase recent research efforts to ensure the interoperability between proposed UAS detect and avoid (DAA) human machine interface requirements (developed within RTCA SC-228) and existing collision avoidance displays. Attendees will be able to view the current state of the art of the DAA pilot traffic, alerting and guidance displays integrated with Traffic advisory and Collision Avoidance (TCAS) II in the UAS-NAS Project's research UAS ground control station (developed in partnership with the Air Force Research Laboratory). In addition, attendees will have the opportunity to interact with the research UAS ground control station and "fly" encounters, using the DAA and TCAS II displays to avoid simulated aircraft. The display of the advisories will be hosted on a laptop with an external 30" monitor, running the Vigilant Spirit system. DAA advisories will be generated by the JADEM software tool, connected to the system via the LVC Gateway. A repeater of the primary flight display will be shown on a 55" monitor mounted on a stand at the back of the booth to show the pilot interaction to the passersby.
NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project is investigating procedures and technologies to facilitate seamless integration of future UAS operations into the NAS. The Tabletop 4 activity solicited subject matter expertise to identify solutions to the potential challenges expected when the remote pilot-to-vehicle ratio scales from 1:1 to m:N, where one or more ground-based pilots control multiple uncrewed aircraft. This presentation details the method and high-level results of the PAAV Tabletop 4 activity.
Topics discussed include: Aeronautics Research Mission Directorate Integrated Systems Research Program (ISRP) and UAS Integration in the NAS Project; UAS Integration into the NAS Project; Separation Assurance and Collision Avoidance; Pilot Aircraft Interface Objectives/Rationale; Communication; Certification; and Integrated Tests and Evaluations.
This report presents the findings from market research conducted for NASA’s Aerial Aid Convergent Aeronautics Solutions (CAS) exploration project, which aims to assess the current state of the market and technological readiness for Uncrewed Aerial Systems (UAS) for medical emergency first response. The research reveals a robust and rapidly growing market for UAS, with a notable emerging sector for Drones as First Responders (DFR). Despite this growth, DFR applications are currently limited by regulatory, technical, and other challenges, which restrict their use primarily to manned remote video surveillance, and therefore are primarily employed by police units. To our knowledge, there is no evidence of UAS being utilized by medical first responders for scene assessment. Limited evidence exists for closely related applications; however, these are mostly confined to pilot programs for the delivery of medical supplies or equipment. Although there has been discussion around fully autonomous DFR applications for medical purposes such as UAS ambulances or patient transport drones, these applications are generally not yet operational in practice. The technology for full autonomy, especially in guidance and control, has seen significant advancements, and recent Federal Aviation Administration (FAA)regulations are likely to accelerate adoption. Computer vision algorithms for fully autonomous medical emergency response scene surveillance are primed for advancement and deployment. A notable gap likely exists between advancements in computer vision research and what is being integrated in the commercial DFR sector. This gap is primarily due to challenges such as quality assurance for autonomous systems, the availability of application-specific training datasets for computer vision algorithms, regulatory constraints, and public perception and privacy concerns.
A fast time simulation was conducted to test the detect and avoid Well Clear definition designed for en route use when an unmanned aircraft (UA) is approaching the landing pattern of the terminal area. Measures focused on were loss of well clear and alerts intended to help the pilot avoid loss of well clear. Data indicated warning-level alerts will occur outside the typical Class D airspace which may prevent the UA from normal operations in the terminal airspace. Other aircraft on 45o entry could result in “nuisance” alerts which may also prevent the UA from normal operations in the terminal airspace. However, eliminating horizontal proximity (τmod) has the potential to increase “nuisance” alerts on the 45o entry and downwind legs. Overall, this suggests that a more stringent definition of Well Clear may be advisable in the landing pattern of the terminal area.
Urban Air Mobility (UAM) refers to a system of air passenger and small cargo transportation within an urban area. The UAM framework also includes other urban Unmanned Aerial Systems (UAS) services that will be supported by a mix of onboard, ground, piloted, and autonomous operations. Over the past few years UAM research has gained wide interest from companies and federal agencies as an on-demand innovative transportation option that can help reduce traffic congestion and pollution as well as increase mobility in metropolitan areas. The concepts of UAM/UAS operation in the National Airspace System (NAS) remains an active area of research to ensure safe and efficient operations. With new developments in smart vehicle design and infrastructure for air traffic management, there is a need for methods to integrate and test various components of the UAM framework. In this work, we report on the development of a virtual reality (VR) testbed using the Cave Automatic Virtual Environment (CAVE) technology for human-automation teaming and airspace operation research of UAM. Using a four-wall projection system with motion capture, the CAVE provides an immersive virtual environment with real-time full body tracking capability. We created a virtual environment consisting of San Francisco city and a vertical take-off-and-landing passenger aircraft that can fly between a downtown location and the San Francisco International Airport. The aircraft can be operated autonomously or manually by a single pilot who maneuvers the aircraft using a flight control joystick. The interior of the aircraft includes a virtual cockpit display with vehicle heading, location, and speed information. The system can record simulation events and flight data for post-processing. The system parameters are customizable for different flight scenarios; hence, the CAVE VR testbed provides a flexible method for development and evaluation of UAM framework.
During the NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) Project’s Technical Capability Level 3 (TCL3) demonstration, a service for stakeholders to share weather and aircraft observations was tested. The overall goal was to increase awareness of airspace and weather activity to increase a pilot’s ability to fly safely. To achieve this goal, a mechanism to share data was created, called “UAS Reports” or UREPs, which were generated by client systems and sent to a central data service. The data service provided subscriptions and allowed for data requests to share the reports that had been sent in by stakeholders. To execute this functionality, four FAA (Federal Aviation Administration)-designated UAS test sites performed UREP testing as part of TCL3. NASA provided the centralized service and test site partners flew missions and simulated activity at the test sites to generate data to send to the service. The loop was closed by having other clients (usually other small UAS operators) request those data from the service or subscribe to feeds from the service. Overall, the tests demonstrated the utility of such a service. In this report, the testing setup, data collection, and analysis of results are presented. The concept of UREPs has since been incorporated as a service within NASA’s Conflict Mitigation Model for UTM. The concept will continue to be tested in NASA’s TCL4 activities.
This document contains a list of human factors guidelines for remote pilot stations (RPS) arranged within an organizing structure. The guidelines are intended for the remote pilot stations (RPSs) of remotely piloted aircraft (RPA) that are capable of operating beyond visual line-of-sight in all airspace classes of the United States National Airspace System (NAS). Numerous human factors guidelines and standards for technological systems have been published by standards agencies and regulatory authorities. In compiling this document, the intent was not to reproduce or re-state existing human factors material. Instead, this document focuses on the unique issues of civilian RPAS, and contains guidelines specific to this sector. As a result, it should be seen as a supplement to existing aviation human factors standards and guidance material. Two constraints were used to focus the scope of this document. First, the assumptions contained in the FAA (2013a) UAS roadmap were used to define the responsibilities that will be assigned to the pilot of a RPAS operating beyond visual line-of-sight in the NAS. This in turn, helped to define the tasks that the remote pilot must perform via the RPS, and thereby the required features and characteristics of the RPS. Second, the points of difference between RPAS and conventional aviation were used to further focus the guidelines on the considerations that make piloting a RPA significantly different to piloting a conventional aircraft. Five broad categories of guidelines are identified. These are (1) performance-based descriptions of pilot tasks that must be accomplished via the RPS, (2) information content of displays, (3) descriptions of control inputs, (4) properties of the interface, and (5) high-level design considerations. Some of the guidelines in this document have been adapted from existing RPAS human factors material from several sources, including RTCA publications and Standardization Agreements (STANAGs) published by the North Atlantic Treaty Organization (NATO).
In order to provide for the safe integration of unmanned aircraft systems (UAS) into the National Airspace System, the command and control communications link connecting the ground-based pilot with the unmanned aircraft must be highly reliable and robust, with national and international standards to enable interoperability and certification. Both line-of-sight (LOS) links using terrestrial-based communications and beyond-line-of-sight (BLOS) links using satellite communications, supported by national and international standards, are required for integrated UAS operations. The National Aeronautics and Space Administration (NASA) has undertaken an extensive technology development and test program in order to provide the required technical data needed to enable C2 standards development. NASAs UAS Integration in the National Airspace System (NAS), or UAS in the NAS Project, included as a major element the Command and Control Communications (C2) Subproject, based at NASAs Glenn Research Center. The successful first phase of the C2 Subproject, completed during 2012-2016, focused primarily on line-of-sight communications. Accomplishments included air-ground channel propagation characterization and modeling; CNPC prototype radio development; CNPC radio flight testing; satellite communications spectrum study and interference analysis; and development of C2 LOS communications standards development. The second phase of the C2 Subproject will focus primarily on beyond-line-of-sight communications, although a follow-on activity for terrestrial LOS communications, known as Terrestrial Extension, is also included. In addition to the terrestrial element, Phase 2 also includes technology development and testing activities for Ka-Band BLOS C2 Satellite Communications; Ku-Band BLOS C2 Satellite Communications; Ku-Band Interference and Propagation; and C-Band Satellite Communications. This paper will provide brief overviews of the C2 Subproject and its Phase I accomplishments, followed by a description of the plans for the C2 Subproject Phase 2.