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This is a presentation to the DOI UAS Interagency group that is informational in nature; just sharing publicly available and previously released information on UAS regulations and some of the UAS operations Langley Center has, to create awareness with other government agencies.
A recent study conducted by the Commercial Aviation Safety Team (CAST) determined 40 percent of all fixed-wing fatal accidents, between 2001 and 2011, were caused by Loss-of-Control (LOC) in flight (National Transportation Safety Board, 2015). Based on their findings, CAST recommended manufacturers develop and implement virtual day-visual meteorological conditions (VMC) display systems, such as synthetic vision or equivalent systems (CAST, 2016). In a 2015 simulation study conducted at NASA Langley Research Center (LaRC), researchers gathered to test and evaluate virtual day-VMC displays under realistic flight operation scenarios capable of inducing reduced attention states in pilots. Each display concept was evaluated to determine its efficacy to improve attitude awareness. During the experiment, Evaluation Pilots (EPs) were shown the following three display concepts on the Primary Flight Display (PFD): Baseline, Synthetic Vision (SV) with color gradient, and SV with texture. The baseline configuration was a standard, conventional 'blue over brown' display. Experiment scenarios were simulated over water to evaluate Unusual Attitude (UA) recovery over 'featureless terrain' environments. Thus, the SV with color gradient configuration presented a 'blue over blue' display with a linear blue color progression, to differentiate attitude changes between sky and ocean. The SV with texture configuration presented a 'blue over blue' display with a black checkerboard texture atop a synthetic ocean. These displays were paired with a Background Attitude Indicator (BAI) concept. The BAI was presented across all four Head-Down Displays (HDDs), displaying a wide field-of-view blue-over-blue attitude indicator. The BAI aligned with the PFD and showed through the background of the navigation displays with opaque transparency. Each EP participated in a two-part experiment series with a total seventy-five trial runs: Part I included a set of twenty-five Unusual Attitude Recovery (UAR) scenarios; Part II included a set of fifty Attitude Memory Recall Tasks (AMRT). At the conclusion of each trial, EPs were asked to complete a set post-run questionnaires. Quantitative results showed that there were no significant statistical effects on UA recovery times when utilizing SV with or without the presence of a BAI. Qualitative results show the SV displays (color, texture) with BAI On are most preferred for both UA recognition and recovery when compared with the baseline display. When only comparing SV display concepts, EPs performed better when using the SV with texture, BAI On, than any other display configuration. This is an interesting find considering most EPs noted their preference towards the SV with color gradient when the BAI was on.
This document examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will deployed into complex systems. A key question for new technologies, is how work will be accomplished by the human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by the designers. The human machine interface (HMI) which is intended to facilitate human-machine interaction and cooperation, however, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture, can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the expected performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements a detect and avoid system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned from a recent research effort in order to improve the methodology for defining technology requirements for regulators in the future. The biggest shortcoming of the presented research program was the absence of the explicit definition, generation and analysis of potential human-automation architectures. Failure to execute this step in the research process resulted in less efficient evaluation of the candidate prototypes technologies in addition to the complete absence of different approaches to human-automation cooperation. For example, all of the prototype technologies that were evaluated in the research program assumed a human-automation architecture that relied on serial processing from the automation to the human. While this type of human-automation architecture is typical across many different technologies and in many different domains, it ignores different architectures where humans and automation work in parallel. Defining potential human-automation architectures a priori also allows regulators to develop scenarios that will stress the performance boundaries of the technology during the evaluation phase. The importance of adding this step of generating and evaluating candidate human-automation architectures prior to formal empirical evaluation is discussed.
NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This video describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the auspices of the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and autonomous detect and avoid functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.
NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This paper describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and contingency control functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.
Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. This airspace integration challenge may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitude - the UAS traffic management (UTM) system - to higher altitudes and new aircraft types, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODM's economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.
Unmanned aircraft (UA) that require access to controlled (or non-segregated) airspace require a highly reliable and robust command and control (C2) link, operating over protected aviation spectrum. While operating within radio line-of-sight (LOS) UA can make use of air-to-ground C2 links to terrestrial stations. When operating beyond LOS (BLOS) where a group of networked terrestrial stations does not exist to provide effective BLOS coverage, a satellite communications link is required. Protected aviation spectrum for satellite C2 links has only recently been allocated in bands where operational satellites exist. A previously existing C-Band allocation covers a bands where there are currently no operational satellites. The new allocations, within the Fixed Satellite Service bands at Ku and Ka-Bands will not be finalized until 2023 due to the need for the development of standards and technical decisions on the operation of UA satellite C2 links within these bands. This paper provides an overview of BLOS satellite C2 links, some of the conditions which will need to be met for the operation of such links, and a look at some aspects of spectrum sharing which may constrain these operations.
Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. This airspace integration challenge may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitudethe UAS traffic management (UTM) systemto higher altitudes and new aircraft types, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODMs economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.
The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.
Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling (JADEM) was developed at NASA Ames Research Center as a research and modeling tool for Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS). UAS will be required to have DAA systems in order to fulfill the regulatory requirement to remain well clear'' of other traffic. JADEM supports research on technological requirements and Minimum Operational Performance Standards (MOPS) for UAS DAA systems by providing a flexible and extensible software platform that includes models and algorithms for all major DAA functions. This paper describes one of these algorithms, the Generic Resolution Advisor and Conflict Evaluator (GRACE). GRACE supports two core DAA functions: threat evaluation and guidance. GRACE is generic in the sense that it is designed to work with any aircraft or sensor type (both cooperative and non-cooperative), and to be used in various applications and DAA guidance concepts, thus supporting evolving MOPS requirements and research. GRACE combines flexibility, robustness, and computational efficiency. It has modest memory requirements and can handle multiple cooperative and noncooperative intruders. GRACE has been used as a core JADEM component in several real-time and fast-time experiments, including human-in-the-loop simulations and live flight tests.
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.
Small, modular aircraft are an emerging technology with a goal to maximize flexibility and enable multi-mission support. This reports the progress of an unmanned aerial system (UAS) project conducted at the NASA Ames Research Center (ARC) in 2016. This interdisciplinary effort builds upon the success of the 2014 FrankenEye project to apply rapid prototyping techniques to UAS, to develop a variety of platforms to host remote sensing instruments. In 2016, ARC received AeroVironment RQ-11A and RQ-11B Raven UAS from the US Department of the Interior, Office of Aviation Services. These aircraft have electric propulsion, a wingspan of roughly 1.3m, and have demonstrated reliability in challenging environments. The Raven airframe is an ideal foundation to construct more complex aircraft, and student interns using 3D printing were able to graft multiple Raven wings and fuselages into FrankenRaven aircraft. Aeronautical analysis shows that the new configuration has enhanced flight time, payload capacity, and distance compared to the original Raven. The FrankenRaven avionics architecture replaces the mil-spec avionics with COTS technology based upon the 3DR Pixhawk PX4 autopilot with a safety multiplexer for failsafe handoff to 2.4 GHz RC control and 915 MHz telemetry. This project demonstrates how design reuse, rapid prototyping, and modular subcomponents can be leveraged into flexible airborne platforms that can host a variety of remote sensing payloads and even multiple payloads. Modularity advances a new paradigm: mass-customization of aircraft around given payload(s). Multi-fuselage designs are currently under development to host a wide variety of payloads including a zenith-pointing spectrometer, a magnetometer, a multi-spectral camera, and a RGB camera. After airworthiness certification, flight readiness review, and test flights are performed at Crows Landing airfield in central California, field data will be taken at Kilauea volcano in Hawaii and other locations.
RTCA (Radio Technical Commission for Aeronautics) Special Committee 228 has initiated a second phase for the development of minimum operational performance standards (MOPS) for UAS (Unmanned Aircraft Systems) detect and avoid (DAA) systems. Technologies to enable UAS with less available Size, Weight, and Power (SWaP) will be considered. A white paper is in development for what topics and issues need to be addressed to develop DAA requirements for low SWAP surveillance systems. This briefing will document the issues to be investigated in SC-228. It will also serve as a review with the committee to get feedback so the white paper can be written and finalized. These topics and issues are not necessarily all the things that NASA will contribute to SC-228 during Phase 2, but what the overall committee needs to accomplish. A portion of the work will be in NASA's UAS in the NAS (National Airspace System) project plan.
Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. These challenge for ODM may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitude the UAS traffic management (UTM) system to higher altitudes and aircraft with humans onboard in controlled airspace, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODMs economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.
The integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) poses a variety of technical challenges to UAS developers and aviation regulators. In response to growing demand for access to civil airspace in the United States, the Federal Aviation Administration (FAA) has produced a roadmap identifying key areas requiring further research and development. One such technical challenge is the development of a "detect and avoid" system (DAA) capable of providing a means of compliance with the "see and avoid" requirement in manned aviation. The purpose of the DAA system is to support the pilot, situated at a ground control station (GCS), in maintaining "DAA well clear" of nearby aircraft through the use of GCS displays and alerts. In addition to its primary function of aiding the pilot in maintaining well clear, the DAA system must also safely interoperate with existing NAS systems and operations, such as the airspace management procedures of air traffic controllers (ATC) and Collision Avoidance (CA) systems currently in use by manned aircraft, namely the Traffic alert and Collision Avoidance System (TCAS) II. It is anticipated that many UAS architectures will integrate both a DAA system and a TCAS II. It is therefore necessary to explicitly study the integration of DAA and TCAS II alerting structures and maneuver guidance formats to ensure that pilots understand the appropriate type and urgency of their response to the various alerts. This paper presents a concept of interoperability for the two systems. The concept was developed with the goal of avoiding any negative impact on the performance level of TCAS II while retaining a DAA system that still effectively enables pilots to maintain DAA well clear.
In order for small but complex systems like rovers, SmallSats, or Unmanned Aircraft (UAS) to operate autonomously, they must have a real-time solution for assessing their own system health. System and Software Health Management (SHM) enables better detection of faulty sensors and software problems, and enables better fault management including mitigation of unpredicted fault scenarios in the absence of a human on-board. In recent work, we have developed a Responsive, Realizable, Unobtrusive Unit (R2U2) for on-board SHM of autonomous UAS and demonstrated its ability to detect faults during flight time. These faults, from sensor failures, to software problems, to malicious security attacks, can present as transient temporal faults that even humans are challenged to find. An R2U2 congfiuration is a modular combination of multiple types of temporal logic runtime observers with fault-specic Bayesian Nets and sensor filters. R2U2 reasons about both on-board hardware and software components; R2U2 itself can be instantiated as an independent FPGA (Field-Programmable Gate Array)-based conguration or as a software component running independently from other software on-board. Small satellites, such as CubeSats, also require on-board SHM and failure mitigation, as limited telemetry bandwidth does not allow the transmission of the entire system state for ground-based health management. However, the autonomous operation of satellites brings a set of challenges different from UAS, including the effects of radiation on non-rad-hard, low-cost components, and the harsher environment of space. We surmise that a new extension of R2U2 could be adapted to help better detect, for example, radiation errors in cheaper COTS (Commercial Off the Shelf) (not rad-hard) components often used in small space systems. Since small satellites often operate in coordination, we will also examine new ways of distributed monitoring of their communication and cooperation and real-time detection of off-nominal situations utilizing multiple satellites. This talk will discuss preliminary work and ideas for building on terrestrial success of system and software health management for the harsher, and differently challenging, environment of space.
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.
NASA's UAS Traffic Management (UTM) project concluded its second flight demonstration activity in late October 2016. This activity demonstrated the capabilities and functionality incorporated into its Technical Capability Level 2 (TCL2) concept, which envisions future operations that are low density, capable of being performed over sparsely populated areas, and allow for a concurrent mix of longer duration, beyond visual-line-of-sight flights and shorter flights within visual-line-of-sight (VLOS). To incorporate these features into a flight demonstration, a scenario-based approach was taken to address different aspects of the TCL2 environment and to meet defined objectives. This paper will describe elements of how the flight activity was conducted and present analyses regarding UTM operations, system messages, and alerting as they pertained to meeting the demonstration objectives and shedding light on research questions and lessons learned.NASA was able to successfully demonstrate complex UTMoperations in a TCL 2 environment in collaboration withindustry partners and the Reno-Stead Airport UAS test range.A scenario-based approach to the demonstration provided arelevant means through which the key elements and objectivesof the test could be captured. Although issues were identifiedthrough the testing and feedback of test participants, theoverall results were in line with the overall UTM objective ofsafely enabling large-scale UAS operations in low altitudeairspace.