The Role of Airspace Management: New Entrants Need Quicker and Sustained Airspace Access
A briefing to FAA and DOD on NASA's current and future Airspace Traffic Management (ATM)/Unmanned Aircraft System Traffic Management (UTM) efforts.
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A briefing to FAA and DOD on NASA's current and future Airspace Traffic Management (ATM)/Unmanned Aircraft System Traffic Management (UTM) efforts.
This manuscript investigates the effects of aircraft health on the surrounding airspace, and proposes a methodology to understand how different aircraft-level faults (system faults, communication faults, etc.) can adversely affect the safety of the airspace, and qualitatively assess the impact of such faults on airspace safety metrics (such as congestion, controller/pilot workload, etc.). The topic of systems health management deals with continuously monitoring the performance of an engineering system, identifying and detecting the presence of faults, predicting the growth/progression of faults, computing the remaining useful life, and aiding online decision-making for the robust, continued operation of such engineering systems. The topic of real-time airspace modeling and safety analysis deals with defining and computing safety metrics for airspace operations in order to support risk-informed decision-making activities for various airspace entities including pilots, air traffic controllers, airlines, etc. This report presents recent research efforts that focus on combining multiple aspects of the aforementioned topics, and investigates the impact of aircraft-level faults on the airspace safety
The emergence and development of advanced technologies and vehicle types has created a growing demand for the introduction of new forms of flight operations. These new and increasingly complex operational paradigms such as Advanced and Urban Air Mobility (AAM/UAM) present regulatory authorities and the aviation community with several design and implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is finding methods to integrate these emerging operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. This paper focus on the development and testing of a prognostic service aimed at estimating the quality of Global Navigation Satellite System (GNSS) performance for an autonomous aircraft in complex environments. The intent of this function is to proactively reduce a flight operations risk of exposure to states that may induce poor or unacceptable navigation system performance by factoring in estimates of GNSS quality into pre-flight and/or in-flight route planning. Methodologies for producing quality estimates are specified and results are provided for selected simulation and flight test cases.
The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.
The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.
The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.
Regulations that establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions. Those requirements will apply to detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the National Airspace System (NAS) and are determined according to their contribution to the overall level of safety required to operate in the airspace. Several key gaps must be addressed in order to link equipment requirements to an airspace level of safety. Foremost among these is the calculation of the relative effectiveness of a particular system to mitigate violations of a separation standard with other aircraft, which is known as the systems risk ratio. The risk ratio is calculated as the probability of mid-air collision with a DAA system divided by the probability of mid-air collision without a DAA system. The risk ratio of a DAA system, in combination with the risk ratios of other collision avoidance mitigations, will determine the overall safety of the airspace measured in terms of the number of mid-air collisions per flight hour. Defining the required risk ratio that the DAA system needs to ensure the safety of the airspace requires an evaluation of the current airspace and a simulated evaluation that incorporates UAS aerodynamic performance and the mission characteristics of future UAS operations that are projected to be conducted in areas that interact with current operations. These evaluations will produce the frequency of encounters that currently exist in the airspace and those that could be generated with the introduction of UAS. Together, the frequency of encounters, an evaluation of unmitigated risk of collision, and a desired level of safety of the airspace will yield a required risk ratio of the DAA system. This study will focus on evaluating the encounter rates between aircraft based on historical radar data and encounter rates that could occur based on simulated UAS missions.
The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.
The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.
The NASA and the FAA have entered into a joint venture to explore, define, design and implement a new airspace management operating concept. The fundamental premise of that concept is that technologies and procedures need to be developed for flight deck and ground operations to improve the efficiency, the predictability, the flexibility and the safety of airspace management and operations. To that end NASA Ames has undertaken an initial development and exploration of "key concepts" in the free flight airspace management technology development. Human Factors issues in automation aiding design, coupled aiding systems between air and ground, communication protocols in distributed decision making, and analytic techniques for definition of concepts of airspace density and operator cognitive load have been undertaken. This paper reports the progress of these efforts, which are not intended to definitively solve the many evolving issues of design for future ATM systems, but to provide preliminary results to chart the parameters of performance and the topology of the analytic effort required. The preliminary research in provision of cockpit display of traffic information, dynamic density definition, distributed decision making, situation awareness models and human performance models is discussed as they focus on the theme of "design requirements".
Underlying all operations in the National Airspace System (NAS) is the concept of safety. Safety, as defined by acceptable levels of risk, is to be maintained at all times. The real-time safety monitoring (RTSM) framework is under development to provide an automated system to quantify safety in the NAS, estimate the current level of safety, and predict the future evolution of safety and the occurrence of events that pose an increased risk to flights so that these occurrences can be managed strategically rather than mitigated reactively. This paper presents the mathematical framework, the models, and the monitoring and prediction algorithms used to achieve this. RTSM computes safety as expressed through a set of safety margins based on user-defined safety metrics, thresolds, and events. Sources of uncertainty are modeled and propagated through the predictions in order to compute the probabilistic evolution of safety and the probability of events that introduce increased risk to operations. A prototype implementation is discussed and results demonstrating feasibility are presented. The results highlight the kinds of predictions that can be computed and the fidelity that is currently achieved.
The topics discussed are the UAS-NAS project life-cycle and ARMD thrust flow down, as well as the UAS environments and how we operate in those environments. NASA's Armstrong Flight Research Center at Edwards, CA, is leading a project designed to help integrate unmanned air vehicles into the world around us. The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS in the NAS, will contribute capabilities designed to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The project falls under the Integrated Systems Research Program office managed at NASA Headquarters by the agency's Aeronautics Research Mission Directorate. NASA's four aeronautics research centers - Armstrong, Ames Research Center, Langley Research Center, and Glenn Research Center - are part of the technology development project. With the use and diversity of unmanned aircraft growing rapidly, new uses for these vehicles are constantly being considered. Unmanned aircraft promise new ways of increasing efficiency, reducing costs, enhancing safety and saving lives 460265main_ED10-0132-16_full.jpg Unmanned aircraft systems such as NASA's Global Hawks (above) and Predator B named Ikhana (below), along with numerous other unmanned aircraft systems large and small, are the prime focus of the UAS in the NAS effort to integrate them into the national airspace. Credits: NASA Photos 710580main_ED07-0243-37_full.jpg The UAS in the NAS project envisions performance-based routine access to all segments of the national airspace for all unmanned aircraft system classes, once all safety-related and technical barriers are overcome. The project will provide critical data to such key stakeholders and customers as the Federal Aviation Administration and RTCA Special Committee 203 (formerly the Radio Technical Commission for Aeronautics) by conducting integrated, relevant system-level tests to adequately address safety and operational challenges of national airspace access by unmanned aircraft systems, or UAS. In the process, the project will work with other key stakeholders to define necessary deliverables and products to help enable such access. Within the project, NASA is focusing on five sub-projects. These five focus areas include assurance of safe separation of unmanned aircraft from manned aircraft when flying in the national airspace; safety-critical command and control systems and radio frequencies to enable safe operation of UAS; human factors issues for ground control stations; airworthiness certification standards for UAS avionics and integrated tests and evaluation designed to determine the viability of emerging UAS technology. Five Focus Areas of the UAS Integration in the NAS Project Separation Assurance Provide an assessment of how planned Next Generation Air Transportation System (NextGen) separation assurance systems, with different functional allocations, perform for UAS in mixed operations with manned aircraft Assess the applicability to UAS and the performance of NASA NextGen separation assurance systems in flight tests with realistic latencies and uncertain trajectories Assess functional allocations ranging from today's ground-based, controller-provided aircraft separation to fully autonomous airborne self-separation Communications Develop data and rationale to obtain appropriate frequency spectrum allocations to enable safe and efficient operation of UAS in the NAS Develop and validate candidate secure safety-critical command and control system/subsystem test equipment for UAS that complies with UAS international/national frequency regulations, standards and recommended practices and minimum operational and aviation system performance standards for UAS Perform analysis to support recommendations for integration of safety-critical command and control systems and air traffic control communications to ensure safe and efficient operation of UAS in the NAS Human Systems Integration Develop a research test bed and database to provide data and proof of concept for GCS - ground control station - operations in the NAS Coordinate with standards organizations to develop human-factors guidelines for GCS operation in the NAS Certification Define a UAS classification scheme and approach to determining Federal Aviation Regulation airworthiness requirements applicable to all UAS digital avionics Provide hazard and risk-related data to support development of type design criteria and best development practices Integrated Tests and Evaluation Integrate and test mature concepts from technical elements to demonstrate and test viability Evaluate the performance of technology development in a relevant environment (full-mission, human-in-the-loop simulations and flight tests)
This document describes a method to demonstrate that a UAS, operating in the NAS, can avoid collisions with an equivalent level of safety compared to a manned aircraft. The method is based on the calculation of a collision probability for a UAS , the calculation of a collision probability for a base line manned aircraft, and the calculation of a risk ratio given by: Risk Ratio = P(collision_UAS)/P(collision_manned). A UAS will achieve an equivalent level of safety for collision risk if the Risk Ratio is less than or equal to one. Calculation of the probability of collision for UAS and manned aircraft is accomplished through event/fault trees.
As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have both an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecasts, predicted health of assets in the airspace, and so on. To this end, we have developed a Real-Time Safety Monitoring (RTSM) that first, estimates the state of the NAS using the dynamic models. Then, given the state estimate and a probability distribution of future inputs to the NAS, the framework predicts the evolution of the NAS, i.e., the future state, and analyzes these future states to predict the occurrence of unsafe events. The entire probability distribution of airspace safety metrics is computed, not just point estimates, without significant assumptions regarding the distribution type and or parameters. We demonstrate our overall approach by predicting the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress.
The National Airspace System undergoes continuous change including in the Upper Class E airspace involving increasingly complex operations and a widening diversity of vehicles. To secure a safe future system, the National Academies recommended an In-time Aviation Safety Management System (IASMS) that is extensible to Upper E. Current Air Traffic Management is not cost-effective to scale for future Upper E operations and diversity of vehicles so the Federal Aviation Administration developed an Upper E Traffic Management ConOps to safely integrate the diverse operations and vehicles having different performance characteristics and flight missions without disrupting current operations including space launch and reentry, suborbital flights, supersonic and hypersonic flights, slow moving or stationary unmanned balloons, and long endurance fixed wing vehicles that are slow, stationary, or high speed. IASMS integrates state-of-the-art predictive modeling with reactive and proactive analytics to detect hazards and mitigate risk precursors for Upper E operators. IASMS identifies emergent safety risks exposed by transformation of the NAS with new and increasingly complex operations. Safety intelligence will also expand the data available and offer insight to new approaches for implementing safety improvements to mitigate risk with more seamless “in-time” integration across the policy, risk management, safety assurance, and promotion pillars of SMS.
The Advanced Capabilities for Emergency Response Operations (ACERO) project is expected to develop, integrate, demonstrate, and transition to operations, evolving aviation technologies from NASA and industry to identify, monitor, and suppress wildland fires as a means to enhance safety, improve operational efficiency, and prevent economic loss. Some of the concepts ACERO explores are: wildfire airspace mangement to improve safety and resource utilization during a disaster, applying new aviation technologies to improve safety and demonstrate new mission-support capabilities, second-shift operations to enable progress towards 24/7 aerial response, and the integration of capabilities across NASA's Aeronautics Research, Science, and Space Technology mission directorates to enable expanded and scalable operations. Realizing this vision is expected to bring positive impact to such areas as: consistency of technology adoption through a unified concept of operations, airspace coordination and deconfliction that integrates portable solutions and enables diverse operations, remote sensing and data fusion for modeling and predictions that support in-time decision making, aircraft technologies for hazard avoidance and state management, and increased response capabilities through persistent communications and surveillance. ACERO continues the research begun under the Scalable Traffic Management for Emergency Response Operations (STEReO) activity, which brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the ACERO and STEReO projects to the Council of Western State Foresters (CWSF) Western State Fire Managers (WSFM) Committee.
Safe operations of aircraft in the National Airspace System (NAS) may be attributed to many factors, including the application of a variety of safety nets (SNs) as a last line of defense. In preparation for the Next Generation Air Transportation System (NextGen), a review of Aviation Safety Reporting System (ASRS) reports for incidents with positive outcomes was conducted to investigate the importance of current safety nets. The examination of positive outcomes not only shows what went wrong, but also what went right to prevent accidents and “save the day.” More than 400 incident reports for 2015 from the voluntary ASRS reporting database were studied in detail to create event sequence diagrams (ESDs), illustrating the effectiveness of SNs. The developed ESDs are considered top-level, representative models and are limited with respect to being reliably quantitative because they are based on only reports from a single year. The ESDs could offer insights into human systems integration research, such as strategically using technologies as SNs without human interface or alleviating human workload with new technologies to provide resilient recovery from off-nominal conditions ensuring flight safety.
As demands increase to use unmanned aircraft systems (UAS) for a broad spectrum of commercial applications, regulatory authorities are examining how to safely integrate them without compromising safety or disrupting traditional airspace operations. For small UAS, several operational rules have been established; e.g., do not operate beyond visual line-of-sight, do not fly within five miles of a commercial airport, do not fly above 400 feet above ground level. Enforcing these rules is challenging for UAS, as evidenced by the number of incident reports received by the Federal Aviation Administration (FAA). This paper reviews the development of an onboard system - Safeguard - designed to monitor and enforce conformance to a set of operational rules defined prior to flight (e.g., geospatial stay-out or stay-in regions, speed limits, and altitude constraints). Unlike typical geofencing or geo-limitation functions, Safeguard operates independently of the off-the-shelf UAS autopilot and is designed in a way that can be realized by a small set of verifiable functions to simplify compliance with existing standards for safety-critical systems (e.g. for spacecraft and manned commercial transportation aircraft systems). A framework is described that decouples the system from any other devices on the UAS as well as introduces complementary positioning source(s) for applications that require integrity and availability beyond what can be provided by the Global Positioning System (GPS). This paper summarizes the progress and test results for Safeguard research and development since presentation of the design concept at the 35th Digital Avionics Systems Conference (DASC '16). Significant accomplishments include completion of software verification and validation in accordance with NASA standards for spacecraft systems (to Class B), development of improved hardware prototypes, development of a simulation platform that allows for hardware-in-the-loop testing and fast-time Monte Carlo evaluations, and flight testing on multiple air vehicles. Integration testing with NASA's UAS Traffic Management (UTM) service-oriented architecture was also demonstrated.