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NASA NTRSDate not supplied

ETM: Upper Class E Traffic Management

The FAA, along with input from the National Aeronautics and Space Administration (NASA) and industry partners, published an initial Concept of Operations (ConOps) for Upper Class E Traffic Management (ETM). To support the next iteration of the ConOps, NASA Ames Research Center has been investigating several technologies and operating principles that will help enable industry in the system development of a cooperative operating environment. Following in the footsteps of the established Unmanned Aircraft Systems Traffic Management (UTM) concept, ETM will utilize some of the basic system architecture and the community-based theories of cooperation and coordination. The main considerations for ETM as compared to UTM, are the diversity of the vehicle types with varying speed and maneuverability capabilities, the severe stratospheric atmosphere conditions, the potential longevity of the missions, and the assorted operating modes (e.g., transit, loitering, or hovering). TM oriented technologies and proposed operating principles are being tested and assessed in a collaborative evaluation of an initial ETM system in spring of 2024. These slides will be presented to a group of stratospheric operators, informing them on some past work and the next steps in the ETM research.

Upper Class-E Traffic Management (ETM)↗
NASA NTRSDate not supplied

Wildland Fire Mitigation: The Role of Airspace Management

Wildland fire is a significant problem on six continents. As wildland fires become increasingly widespread, dangerous, and costly, advances in aerial technology will make a significant difference. Leveraging Unmanned Aircraft Systems Traffic Management (UTM) success, NASA is conducting aerial suppression research and development (R&D) and is collaborating across government, industry, and the academic community to co-develop cutting-edge technology, procedures, and best practices. Join Dr. Parimal "PK" Kopardekar, Director of the NASA Aeronautics Research Institute (NARI), and learn more about how to maximize the utilization of airspace for wildfire management and mitigation.

Wildland fire↗
NASA NTRSDate not supplied

Future Airspace Operations: UTM-Inspired Air Traffic Management

We need to prepare airspace system to accommodate diversity, density and complexity of future operations. Current system will reach its peak due to use of old technology and human-in-the-loop nature to accommodate new entrants. Talk will focus on how an ATM system can be made ready to meet the future needs. Author will discuss a number of lessons based on Unmanned Aircraft System Traffic Management (UTM) could be leveraged to prepare for future.

future airspace operations↗
NASA NTRSDate not supplied

Extensible Traffic Management (xTM) - High-altitude Operations and Beyond

The technology development of balloons, airships, and high-altitude long-endurance (HALE) high-aspect-ratio wing aerial vehicles has expedited the deployment of high-altitude operations above Flight Level (FL) 600. It allows broader communication service area coverage than at ground level and enables efficient and precise earth observation to help address global climate change. Meanwhile, a record number of orbital launches were conducted in 2021. New mission concepts including those for small satellites, satellite constellations, suborbital tourism and point to point cargo transport are being developed. To enable efficient and safe operations of new-entrant vehicles and to alleviate the potential burden on air traffic controllers, the concept of Unmanned aircraft systems Traffic Management (UTM) explored a different approach requiring cooperative operations among operators/pilots through operational intent sharing and coordination. This concept has been extended and proposed by the community to handle traffic management for high-altitude operations. While the concept and basic system were tested in UTM, there are many critical capabilities needed for high-altitude operations. This talk will introduce the challenges brought by high-altitude operations and space operations and on-going research activities in developing critical capabilities for extensible traffic management at NASA.

Extensible Traffic Management↗
NASA NTRS2017

UAV Trajectory Modeling Using Neural Networks

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural network should be able to predict the vehicle's future states at next time step. A complete 4-D trajectory are then generated step by step using the trained neural network. Experiments in this work show that the neural network can approximate the sUAV's model and predict the trajectory accurately.

Neural Networks↗
NASA NTRS2018

Fe(3): An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Collision Avoidance↗
NASA NTRS2018

Fe3: An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Trajectory Modeling↗
NASA NTRS2018

UTM RTT CWG Concept & Use Cases Package #2

The Concept & Use Cases Package #2: Technical Capability Level 3 document represents the collaborative research efforts between the FAA and NASA as joint members of the Unmanned Aircraft System Traffic Management (UTM) Research Transition Team (RTT). Contained in this document are the 1) Terms and Definitions, 2) Foundational Principles, 3) Concept Narratives, 4) Use Cases, 5) Operational Views, and 6) Roles and Responsibilities of actors interacting within what is considered to be encompassed by Technical Capability Level 3 UTM operating environments. The contents of Package #2 should NOT be considered established policy or construed as regulatory in nature. What is presented is meant to communicate the current, agreed upon understanding between the FAA and NASA on particular features of UTM as exemplified through use cases and concept narratives for the purposes of supporting joint NASA/Industry Demonstrations and the UTM Pilot Program. It is also meant to foster discussion and refinement of the concepts and approaches being pursued by the other RTT working groups.

RTT↗
NASA NTRS2020

New Flight Rules to Enable the Era of Aerial Mobility in the National Airspace System

In the 21st Century, new aviation markets, vehicle types, and technologies are fast emerging, inspiring new operational concepts for the National Airspace System such as Unmanned Aircraft Systems Traffic Management and Urban Air Mobility. These novel operations envision a dramatic increase in aerial mobility, or the ability to navigate freely through the airspace with unprecedented access and operational flexibility. Implementing these concepts presents a major challenge to the existing operational modes of Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), developed under the limitations of early 20th Century technology and procedures to ensure safe navigation and separation from traffic. To meet this challenge and to support the needs of operators in the 21st Century and beyond, this paper proposes that VFR and IFR be augmented by new flight rules – Digital Flight Rules (DFR) – that leverage modern and emerging technologies and are not bound by restrictions borne of the state of technology 75-100 years ago. The objective of DFR is to provide safe and unfettered access to the airspace to all participating vehicle operators under all visibility conditions without incurring the limitations in operational flexibility inherent to IFR and even VFR. Advancements in communications, navigation, surveillance, aircraft connectivity, information access, automation technology, and supporting ground infrastructure provide the opportunity for the vehicle operator to engage at an unprecedented level in managing their flights regardless of flight visibility. Under DFR, these advancements enable the vehicle operator to assume full responsibility for traffic separation and therefore full trajectory management authority in all visibility conditions and airspace regions. The changes in roles and responsibilities are expected to enable greater airspace access and operational flexibility than afforded by IFR and VFR, thus enabling the emergence of new operations and a new era of advanced aerial mobility.

Mobility↗
NASA NTRSDate not supplied

Digital Flight: Enabling the Era of Scalable Mobility in the National Airspace System

In the 21st Century, new aviation markets, vehicle types, and technologies are fast emerging, inspiring new operational concepts for the National Airspace System such as Unmanned Aircraft Systems Traffic Management and Urban Air Mobility. These novel operations envision a dramatic increase in aerial mobility, or the ability to navigate freely through the airspace with unprecedented access and operational flexibility. Implementing these concepts presents a major challenge to the existing operational modes of Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), developed under the limitations of early 20th Century technology and procedures to ensure safe navigation and separation from traffic. To meet this challenge and to support the needs of operators in the 21st Century and beyond, this paper proposes that VFR and IFR be augmented by new flight rules – Digital Flight Rules (DFR) – that leverage modern and emerging technologies and are not bound by restrictions borne of the state of technology 75-100 years ago. The objective of DFR is to provide safe and unfettered access to the airspace to all participating vehicle operators under all visibility conditions without incurring the limitations in operational flexibility inherent to IFR and even VFR. Advancements in communications, navigation, surveillance, aircraft connectivity, information access, automation technology, and supporting ground infrastructure provide the opportunity for the vehicle operator to engage at an unprecedented level in managing their flights regardless of flight visibility. Under DFR, these advancements enable the vehicle operator to assume full responsibility for traffic separation and therefore full trajectory management authority in all visibility conditions and airspace regions. The changes in roles and responsibilities are expected to enable greater airspace access and operational flexibility than afforded by IFR and VFR, thus enabling the emergence of new operations and a new era of advanced aerial mobility.

Mobility↗
NASA NTRSDate not supplied

Traffic Flow Analysis for Package Delivery Drones using a Queueing Model

A key component of the small unmanned aircraft systems traffic management ecosystem is the design of scalable algorithms for strategic deconfliction of drones prior to takeoff. In this work, we focus on efficient flow management of drones on a network of intersecting edges subject to two kinds of spacing constraints: 1) between any two adjacent vehicles on an edge and 2) between any two vehicles on two different edges arriving one after the other at an intersection. The spacing is designed to enable non-intersection of operational volumes corresponding to two different vehicles thereby properly separating the vehicles inside each volume. For simplicity, we assume a constant ground speed for the drones and fixed dimensions for the operational volume blocks. The deconfliction is managed by adjusting the takeoff time of the drones, thereby regulating their arrival time at various crossing waypoints in the network. This framework allows us to study the maximum flow (throughput) of vehicles on a network of edges connecting depots to drop off sites subject to the temporal spacing constraints. The departure scheduling of individual drones results in a combinatorial optimization problem. To alleviate this, we solve a max-flow formulation and use queueing theory to simplify the analysis and provide upper bounds to the underlying optimization problem for individual drone departure scheduling. Our results indicate that throughput drops rapidly after the density of drones in the network passes the max-flow limits.

Alexey A Munishkin↗
NASA NTRS2016

Applying Required Navigation Performance Concept for Traffic Management of Small Unmanned Aircraft Systems

In anticipation of a rapid increase in the number of civil Unmanned Aircraft System(UAS) operations, NASA is researching prototype technologies for a UAS Traffic Management (UTM) system that will investigate airspace integration requirements for enabling safe, efficient low-altitude operations. One aspect a UTM system must consider is the correlation between UAS operations (such as vehicles, operation areas and durations), UAS performance requirements, and the risk to people and property in the operational area. This paper investigates the potential application of the International Civil Aviation Organizations (ICAO) Required Navigation Performance (RNP) concept to relate operational risk with trajectory conformance requirements. The approach is to first define a method to quantify operational risk and then define the RNP level requirement as a function of the operational risk. Greater operational risk corresponds to more accurate RNP level, or smaller tolerable Total System Error (TSE). Data from 19 small UAS flights are used to develop and validate a formula that defines this relationship. An approach to assessing UAS-RNP conformance capability using vehicle modeling and wind field simulation is developed to investigate how this formula may be applied in a future UTM system. The results indicate the modeled vehicles flight path is robust to the simulated wind variation, and it can meet RNP level requirements calculated by the formula. The results also indicate how vehicle-modeling fidelity may be improved to adequately verify assessed RNP level.

required navigation performance↗
NASA NTRS2022

Overview of NASA’s Extensible Traffic Management (xTM) Research

NASA’s Unmanned Aircraft Systems (UAS) Traffic Management (UTM) project introduced a new Air Traffic Management (ATM) architecture that utilizes industry’s ability to supply industry-developed, third-party services that work complementarily with the FAA-provided Air Traffic Service (ATS) to exchange relevant air vehicle information among the UAS operations and between the UTM and the conventional ATM system. The UTM architecture was used to successfully demonstrate the feasibility of safe, efficient, and scalable small UAS operations in low altitudes below 400 feet above ground level. Following the success and adoption of UTM architecture, the foundational UTM requirements and core properties were generalized to become Extensible Traffic Management (xTM) requirements to support operations of new entrants beyond small UAS, such as operations in high altitudes over 60,000 feet, designated as upper Class E in the United States National Airspace System (NAS). In this paper, the generalization of UTM to xTM and NASA’s approach for developing an xTM system for upper Class E Traffic Management (ETM) are discussed. The paper also discusses the planned research to examine the potential xTM-Air Traffic Control (ATC) interactions across multiple xTM systems and identify common coordination procedures, ATC roles/responsibilities, and data exchange requirements. This work is one of the steps for improving interoperability between the xTM systems and ATS, which is critical for safe and efficient sharing of the airspace among the new entrants served by the xTM systems and conventional ATS-serviced operations.

air traffic management↗
NASA NTRS2020

Strategic Deconfliction Performance: Results and Analysis from the NASA UTM Technical Capability Level 4 Demonstration

Unmanned Aircraft System (UAS) Traffic Management (UTM) refers to the service-based, cooperative approach to the management of small UAS in the National Airspace System that is safe, scalable, and fair. UTM provides the means to manage the airspace in a complementary manner that does not burden the current air traffic control workforce or infrastructure but allows the Air Navigation Service Provider to maintain its regulatory and operational authority of the airspace. A key feature of UTM is the ability to provide operators the means to strategically deconflict operations from others in the airspace through the digital exchange of information via supporting services. Through this approach, the four-dimensional operation volumes that encompass the intent of operators in a given area are discoverable and can be used for airspace awareness as well as planning conflict free operations that account for and avoid other operations. In certain cases, it is also possible to negotiate volume intersections for shared airspace use without the need to re-plan. In the NASA UTM concept, strategic deconfliction is the first layer of three in the overall conflict management model. The three layers of the conflict management model, which follow the International Civil Aviation Organization’s scheme [ICAO 2005] are: strategic conflict management, separate provision, and collision avoidance. In UTM, the strategic layer mostly occurs prior to departure, but is applicable to en route operations with sufficient planning horizon. The initial requirements for a strategic deconfliction capability within UTM are defined in a NASA publication [Rios 2018]. Within the concept and implementation of service-provided strategic deconfliction is the notion of priority. It is understood that there are instances in which an operation requires a priority designation within the UTM system and special handling accordingly to provide situation awareness and facilitate appropriate responses from other airspace users. Examples of situations requiring priority designation include: when an operator declares an emergency due to problems with the vehicle or its immediate surroundings; operations that are in support of certain organizations (e.g., public safety and first responders); or special missions that also require priority use of airspace (e.g., emergency medical deliveries). UAS Volume Reservations (UVRs) also relate to the topic of priority in the sense that the airspace that the volume encompasses has a different status or classification in which unassociated operations must vacate if inside, or avoid if outside, through strategic deconfliction with the volume. Operations that are specially permitted to access the UVR area are typically assigned priority status given the nature of their mission and their associated credentials. The ability to perform strategic deconfliction, handle certain operations with a priority distinction, and establish UVRs that are communicated throughout the UTM system, is predicated on an architecture that has been established through an evolutionary process in response to close collaboration with stakeholders from government and industry. Another important and influential aspect of these capabilities and architecture is the live, distributed flight tests that have been conducted across the Technical Capability Levels (TCLs) that culminated with a set of complex tests performed as part of TCL4 [Rios 2020]. The TCL4 flight test involved two FAA-designated UAS test sites building teams to collaborate with NASA’s UTM Project on the execution of several detailed, small UAS scenarios in urban environments.

conflict management↗
NASA NTRSDate not supplied

Identifying Common Use Cases across Extensible Traffic Management (xTM) for Interactions with Air Traffic Controllers

NASA’s Extensible Traffic Management (xTM) builds on the foundation and the architecture of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concept and extends it broadly to other domains, such as Advanced / Urban Air Mobility (AAM/UAM) and Upper Class E Traffic Management (ETM). These xTM concepts assume the ability to fly in airspace that is authorized to operate solely under xTM services and mostly without any air traffic control (ATC) support. However, they also assume circumstances in which the xTM vehicles would need to operate in conventional ATC-managed airspace, both during nominal and off-nominal scenarios. Due to the vast differences in the xTM vehicle performances and missions, there is a concern that ATC may have difficulty in safely managing the xTM traffic and providing appropriate services to all vehicles, unless a consistent set of roles, procedures, and data exchange requirements are defined across the diverse set of xTM vehicle operations. In this paper, we describe a set of use cases that have been identified in UTM, AAM/UAM, and ETM operations that are related to ATC interactions, and we propose to categorize these use cases across xTM domains based on common trigger events. Organizing the use cases from the perspective of ATC roles per each trigger event is expected to provide the first step in discovering common procedures and data requirements across xTM domains that could help ease the controllers’ cognitive task load and allow them to manage these interactions more safely.

Extensible Traffic Management (xTM)↗
NASA NTRS2022

Spectrum Research for Aviation Final Report

Task TO-G-026 was established to identify possible spectrum allocations to support the Scalable Traffic Management for Emergency Response Operations (STEReO) Project’s approach of applying Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concepts to the management of disaster response. Both large and small unmanned aircraft have been found to provide significant benefits in disaster response. However, application of unmanned aircraft is limited by the difficulty in managing disaster area airspace. UTM concepts can greatly increase the ability to safely apply UAS to many disaster response requirements. The use of UAS requires communication links to provide command and control, telemetry, delivery of mission payload data, and situational awareness/navigation functionality to enable safe operations. The outcome of Task TO-G-026 research provides guidance in identifying appropriate potential spectrum bands required to support STEReO disaster response operations. This report presents these research results.

Robert J. Kerczewski↗