SEARCH · Engineering Papers

Results for “Airspace”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

NASA NTRS2017

Enabling Airspace Integration for High Density Urban Air Mobility

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.

Mueller, Eric Richard↗

NASA NTRS2019

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project

Phase 1 of the UAS-NAS (Unmanned Aircraft Systems-National Airspace System) project focused on MOPS (Minimum Operational Performance Standards) development for large UAS transitioning through Class D, E, and G airspace. Phase 2 activities are currently focused on extended UAS operations in Class D, E, and G airspace, as well as sensors and architectures that will enable DAA (Detect and Avoid) equipment to be installed on a wider range of UAS. Encounters with non-cooperative intruders in low altitude airspace under 10,000 feet will be explored for UAS with a low Size, Weight, and Power (SWaP) radar. New sensors for detecting non-cooperative intruder aircraft will have a more limited detection range and field of regard; therefore, the analysis of non-cooperative encounter geometries may help in developing the requirements for an onboard low SWaP radar (and electro-optical sensor). The current simulation, led by HSI (Human Systems Integration Division at NASA Ames Research Center) as part of the DAA subproject, will support efforts toward developing a modified DAA Well Clear (DWC) definition that would be more appropriate for UAS equipped with limited surveillance and aircraft performance capabilities compared to the Phase 1 DAA system. The findings will inform Phase 2 display requirements for alternative surveillance use cases.

Collision Avoidance↗

NASA NTRS2018

Enabling Airspace Integration for High Density Urban Air Mobility 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 overly burden traditional airspace users and air traffic control. These challenges 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 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.

Mueller, Eric↗

NASA NTRS2019

Application of AI in the NAS - the Rationale for AI-Enhanced Airspace Management

This paper extends on the initial findings of "Application of Artificial Intelligence in the National Airspace System: A Primer" (Stroup & Niewoehner: Herndon, VA; ICNS-2019), and looks at why the current technologies, enterprise architecture, and future program plans may not be enough to address persistent operational challenges. This paper further explores why emergent operational concepts, business models, and demand profiles may necessitate AI-enhanced Communications, Navigation and Communications (CNS) infrastructure to disrupt current operational impediments. European airspace, as well as the NAS, has similar challenges. Key challenges explored in this study include: quantifiable improvements to NAS capacity, efficiency, and resiliency; traffic flow management of diverse users; UTM-ATM airspace integration; equitable access to airspace; and airborne-ground interoperability of AI applications. Finally, we examine why trustworthiness and resiliency will be key mileposts on the regulatory pathway to AI certification.

Aviation↗

NASA NTRS2020

Adaptive Airborne Separation to Enable UAM Autonomy in Mixed Airspace

The excitement and promise generated by Urban Air Mobility (UAM) concepts have inspired both new entrants and large aerospace companies throughout the world to invest hundreds of millions in research and development of air vehicles, both piloted and unpiloted, to fulfill these dreams. The management and separation of all these new aircraft have received much less attention, however, and even though NASA’s lead is advancing some promising concepts for Unmanned Aircraft Systems (UAS) Traffic Management (UTM), most operations today are limited to line of sight with the vehicle, airspace reservation and geofencing of individual flights. Various schemes have been proposed to control this new traffic, some modeled after conventional air traffic control and some proposing fully automatic management, either from a ground-based entity or carried out on board among the vehicles themselves. Previous work has examined vehicle-based traffic management in the very low altitude airspace within a metroplex called UTM airspace in which piloted traffic is rare. A management scheme was proposed in that work that takes advantage of the homogeneous nature of the traffic operating in UTM airspace. This paper expands that concept to include a traffic management plan usable at all altitudes desired for electric Vertical Takeoff and Landing urban and short-distance, inter-city transportation. The interactions with piloted aircraft operating under both visual and instrument flight rules are analyzed, and the role of Air Traffic Control services in the postulated mixed traffic environment is covered. Separation values that adapt to each type of traffic encounter are proposed, and the relationship between required airborne surveillance range and closure speed is given. Finally, realistic scenarios are presented illustrating how this concept can reliably handle the density and traffic mix that fully implemented and successful UAM operations would entail.

Cotton, William B.↗

NASA NTRS2020

Airspace Operations: Vision for 2045 and Beyond

We are seeing interesting changes in airspace operations. We are experiencing growth in global aviation for passenger and cargo travel. At the same time, drones of all sizes, urban air mobility, electric aircraft, commercial space transportation, supersonics, hypersonics, and increasingly autonomous vehicles will continue to mature. These operations along with current aviation will require access to airspace operations. Such access and scalability needs will only continue to increase in the future. Given that systems and procedures that will enable and support the future density and diversity takes a considerable amount of time to build and harmonize across the globe, it is appropriate that research efforts to enable 2045 operations begin now. A perfect storm is brewing as a number of factors are coming together, including: anticipated growth in diversity and density; limitations of our current system to support the growth and diversity; lack of utilization of latest technologies in an increasingly digitized world to support air traffic management; and a long lead time to conduct research, develop requirements, and built and deploy air traffic management systems. All these factors indicate that now is the time to start thinking about the needs of 2045 and beyond. In a limited manner, Unmanned Aircraft System Traffic Management (UTM) has shown that new thinking and implementation paths for airspace operations is possible. The current system as it exists is based on many assumptions and limitations of technologies (e.g., radar, human-centered voice communications) which may not be true moving forward given the technologies around us are changing. The panel will discuss the following and related topics: 1. Expected growth in density, diversity, and needed scalability, 2. Likely requirements of air traffic management system to enable and support 2045 and beyond operations, 3. Assumptions related to air traffic management and operations that need to reevaluated based on technology trends, 4. Identification of research priorities and harmonization of research across the globe, and 5. Transition approaches from current air traffic operations to new vision 2045. The panel discussion will be useful for global air traffic management researchers, managers, strategists, airspace users, air traffic management system developers and integrators, and academic researchers.

Kopardekar, Parimal H.↗

NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) subproject aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-TheLoop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and MultiAircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

Advanced Air Mobility↗

NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) sub- project aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-The- Loop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and Multi- Aircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

advanced air mobility↗

NASA NTRS2024

A Fair, Economically-Efficient, Incentive-Aligned, Scalable Airspace Auction Mechanism for UAV Traffic Management

Unmanned Aerial Vehicles (UAVs) are increasingly used in a wide range of applications such as cinematography, package delivery, and surveying. As a result, regulators have become interested in developing UAV Traffic Management (UTM) systems to coordinate UAV traffic. One possible framework for UTM is a combinatorial auction. Under this framework, airspace is modeled as a grid of space-time cells. UAV operators bid on sets of cells which collectively form flight paths for their UAVs. An ideal airspace auction should: be fair, be incentive-aligned, be scalable, allocate airspace economically-efficiently, enable price discovery, and reduce the work required to participate where possible. In this paper, we propose the first auction mechanism for airspace allocation that meets the criteria above. Our mechanism: (a) is provably economically-efficient, fair and incentive-aligned, (b) shares pricing information with bidders and (c) has features which reduce the burden of participating. We evaluate our mechanism on scenarios based on a Japan Aerospace Exploration Agency (JAXA) case study and find that it can scale to 26,000 bids.

Robert Allan Morris↗

NASA NTRS2024

Operational Integration Assessment (OIA) of Midterm UAM Operations: Class C Airspace Tabletop Exercise and Integration Checkpoint

The National Aeronautics and Space Administration (NASA), in collaboration with the Federal Aviation Administration (FAA), is conducting research into evolving today’s air traffic management system towards a more automated and operationally flexible airspace to accommodate Urban Air Mobility (UAM) operations at scale. UAM operations, enabled by electric Vertical Takeoff and Landing (eVTOL) aircraft, may change the role of aviation in the movement of people and goods and provide practical, cost-effective air transport in metropolitan areas. FAA UAM Concept of Operations v2.0 describes three evolutionary stages of UAM operations: Initial, Midterm, and Mature State operations. Midterm operations are comprised of many complex changes to the national airspace system (NAS). The Operational Integration Assessment (OIA) was created as a capability to address the need to study the progression and identify interdependencies of those changes that may occur during the midterm UAM operations timeframe. The OIA includes a series of tabletop exercises and integration checkpoints planned to explore various use cases from end-to-end, evaluated by NASA’s Air Traffic Management eXploration (ATM-X) project in partnership with the FAA’s William J. Hughes Technical Center (WJHTC) and industry partners. The use cases were exercised in an immersive, integrated live-virtual-constructive (LVC) airspace simulation environment, called the NASA/FAA Laboratory Integrated Test Environment (NFLITE), as part of an effort to learn how UAM operations can scale beyond the as-is NAS and through the transition to higher-tempo and highly automated operations of the future. This document describes the events of the tabletop exercise held from January 24-26, 2023, at the National Airspace Research & Technology Park (NARTP) in Egg Harbor Township, New Jersey, adjacent to the WJHTC and the subsequent integration checkpoint performed on March 28, 2023,at NASA Langley Research Center (LaRC) in Hampton, Virginia.

UAM↗

NASA NTRS2024

Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control

Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.

Regina Ayoubi↗

NASA NTRS2013

Generic Airspace Survey

This paper reports on an extension of generic airspace research to explore the amount of memorization and specialized skills required to manage sectors with specific characteristics or factors. Fifty-five retired controllers were given an electronic survey where they rated the amount of memorization or specialized skills needed for sixteen generic airspace factors. The results suggested similarities in the pattern of ratings between different areas of the US (East, Central, and West). The average of the ratings for each area also showed some differences between regions, with ratings being generally higher in the East area. All sixteen factors were rated as moderately to highly important and may be useful for future research on generic airspace, air traffic controller workload, etc.

generic airspace↗

NASA NTRSDate not supplied

Theoretical and Simulated Capacity of Urban Air Mobility Airspace Characteristics

As interest in urban air mobility grows, as are the optimistic predictions for potentially hundreds of simultaneous operations within a given metropolitan airspace. This high density of traffic poses a challenge for safe, efficient, and timely operations, particularly when realistic airspace restrictions, fleet sizes, and fluctuating demand are considered. Routes for urban air mobility aircraft, similar to automotive roadways more than other types of airways, are one proposed solution for traffic management. This paper identifies several potential components of urban air mobility routes and compares their numerically predicted maximum capacity with what is achieved in a realistic simulation that includes airspace restrictions, parking limitations, fleet sizes, and uneven demand.

Urban Air Mobility↗

NASA NTRSDate not supplied

Theoretical and Simulated Capacity of Urban Air Mobility Airspace Characteristics

Urban Air Mobility↗

NASA NTRS2023

Study of Pairwise Deconfliction Metrics to Analyze Air Traffic Complexity in Upper Class E Airspace

Upper Class E Traffic Management (ETM) is envisioned to cooperatively facilitate operations of a diverse set of aerial vehicles, such as high-altitude long-endurance fixed-wing unmanned aircraft (low-speed and high-speed), high-altitude platforms, airships, stratospheric balloons, supersonic unmanned and commercial aircraft, etc., with a wide variety of mission types, performance characteristics, communication, navigation and surveillance capabilities, maneuverability, and on-board avionics in the National Airspace System (NAS) ’above’ 60,000 feet above mean sea level, without an active and direct control from human air traffic controllers. A diverse mixture of aerial vehicle types creates significant challenges in understanding air traffic complexity, which may not correlate strongly with air traffic density. One key step for determining air traffic complexity in upper class E airspace is to first understand pairwise deconfliction metrics such as reachability, reserve area, and reserve flight time for each pair of unique aerial vehicle types under potential conflict. Therefore, pairwise deconfliction metrics are first defined, and analytical equations are derived for conflict resolution using the heading change maneuver. Next, case studies are performed to analyze deconfliction metrics to avoid secondary conflicts in upper class E airspace. The study shows that pairwise deconfliction metrics are functions of maneuverability, performance characteristics, uncertainty in position and velocity, heading angle change, and conflict angle of aerial vehicles. The next step for this research is to build a mathematical model for air traffic complexity using pairwise deconfliction metrics and validate it in an upper Class E simulation environment.

Airspace Complexity↗

NASA NTRSDate not supplied

Study of Pairwise Deconfliction Metrics to Analyze Air Traffic Complexity in Upper Class E Airspace

Airspace Complexity↗

NASA NTRS2013

Scheduling and Separating Departures Crossing Arrival Flows in Shared Airspace

Flight efficiency and reduction of flight delays are among the primary goals of NextGen. In this paper, we propose a concept of shared airspace where departures fly across arrival flows, provided gaps are available in these flows. We have explored solutions to separate departures temporally from arrival traffic and pre-arranged procedures to support controllers' decisions. We conducted a Human-in-the-Loop simulation and assessed the efficiency and safety of 96 departures from the San Jose airport (SJC) climbing across the arrival airspace of the Oakland and San Francisco arrival flows. In our simulation, the SJC tower had a tool to schedule departures to fly across predicted gaps in the arrival flow. When departures were mistimed and separation could not be ensured, a safe but less efficient route was provided to the departures to fly under the arrival flows. A coordination using a point-out procedure allowed the arrival controller to control the SJC departures right after takeoff. We manipulated the accuracy of departure time (accurate vs. inaccurate) as well as which sector took control of the departures after takeoff (departure vs. arrival sector) in a 2x2 full factorial plan. Results show that coordination time decreased and climb efficiency increased when the arrival sector controlled the aircraft right after takeoff. Also, climb efficiency increased when the departure times were more accurate. Coordination was shown to be a critical component of tactical operations in shared airspace. Although workload, coordination, and safety were judged by controllers as acceptable in the simulation, it appears that in the field, controllers would need improved tools and coordination procedures to support this procedure.

shared airspace↗

NASA NTRS2014

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

air traffic optimization↗