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At least 145 records · Page 8

Enabling Airspace Integration for High-Density On-Demand 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 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.

Mueller, Eric↗

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↗

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↗

Aircraft Classification Using Radar from Small Unmanned Aerial Systems for Scalable Traffic Management Emergency Response Operations

This work investigates two machine learning techniques: Support Vector Machine (SVM) and Autoencoders (AE)with SVM layer for classification of radar trajectories as General Aviation (GA), fixed-wing small Unmanned Aerial System (sUAS), or not-an-aircraft using radar data recorded from sUAS. Onboard identification of intruder aircraft type is useful for planning avoidance maneuvers and is necessary to provide autonomous systems to meet or exceed the avoidance capability of a human pilot. Aircraft classification can identify intruder aircraft that are not part of the team and may be violating a Temporary Flight Restriction. Aircraft classification is needed in monitoring an airspace where multiple aircraft are teaming on a shared task. Scalable Traffic Management for Emergency Response Operations (STEReO) is a NASA project aimed at improving disaster response by enabling large scale aircraft operations through the teaming of manned aircraft with sUAS to maximize emergency response resources. To this end, this work uses trajectories and radar derived features to classify aircraft from a multirotor sUAS. The AE + SVM generated the strongest classification overall accuracy of 93.5% using the first 4 seconds of radar track data for tracks that activated the avoidance system. Subsampling the available track data increased the available training data with the maximum aircraft recall of 0.94 achieved using the SVM with 1 second track data.

Chester V. Dolph↗

Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations

The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.

communication link modeling↗

Air Traffic Controller Acceptability of Unmanned Aircraft System Detect-and-Avoid Thresholds

A human-in-the-loop experiment was conducted with 15 retired air traffic controllers to investigate two research questions: (a) what procedures are appropriate for the use of unmanned aircraft system (UAS) detect-and-avoid systems, and (b) how long in advance of a predicted close encounter should pilots request or execute a separation maneuver. The controller participants managed a busy Oakland air route traffic control sector with mixed commercial/general aviation and manned/UAS traffic, providing separation services, miles-in-trail restrictions and issuing traffic advisories. Controllers filled out post-scenario and post-simulation questionnaires, and metrics were collected on the acceptability of procedural options and temporal thresholds. The states of aircraft were also recorded when controllers issued traffic advisories. Subjective feedback indicated a strong preference for pilots to request maneuvers to remain well clear from intruder aircraft rather than deviate from their IFR clearance. Controllers also reported that maneuvering at 120 seconds until closest point of approach (CPA) was too early; maneuvers executed with less than 90 seconds until CPA were more acceptable. The magnitudes of the requested maneuvers were frequently judged to be too large, indicating a possible discrepancy between the quantitative UAS well clear standard and the one employed subjectively by manned pilots. The ranges between pairs of aircraft and the times to CPA at which traffic advisories were issued were used to construct empirical probability distributions of those metrics. Given these distributions, we propose that UAS pilots wait until an intruder aircraft is approximately 80 seconds to CPA or 6 nmi away before requesting a maneuver, and maneuver immediately if the intruder is within 60 seconds and 4 nmi. These thresholds should make the use of UAS detect and avoid systems compatible with current airspace procedures and controller expectations.

unmanned aircraft systems↗

Urban Air Mobility Traffic Analysis Tool for Airspace Involving Vertiport Hub Operations to Examine Simulated Conflicts

Presented herein are details of the development of an Urban Air Mobility Traffic Analysis Tool (UAM TAT), designed to analyze the traffic of Vertical Take-off and Landing (VTOL) air-craft in urban agglomerations to enable the Urban Air Mobility(UAM) operations. The tool aims to address challenges of UAM operations in a simulated airspace by testing different scenarios and methods for air traffic management. It emphasizes the need for effective risk management practices and methodologies to ensure the safety of operations, given the increasing use of highly automated aircraft (i.e., Advanced Air Mobility (AAM))in urban environments. The tool is modular and allows for the simulation of various families of VTOLs and different air traffic rules, making it suitable for defining and estimating airspace and vertiports capacity, determining VTOL requirements, and testing and comparing air traffic management methods. The results of five different simulations are presented that show the capabilities and functionalities of the tool. The simulations present the impact of vertiport hub operations and various ATM approach on the VTOLs’ conflicts.

Urban Air Mobility↗

UTM Technical Capability Level 4 Testing

NASA's UTM project is conducting research on a traffic management concept for small unmanned aircraft systems (UAS) flying in low altitude, uncontrolled airspace. The project started in 2015 and is developing prototype UTM systems of successively complex technical capability levels (TCL) that are tested in the field. To date TCL levels 1-3 have been tested and TCL 4 will be tested in the summer of 2019. Project results are transferred to the FAA and industry to advance the adoption, implementation, and design standards of future UTM systems.

Johnson, Ronald D.↗

Exploration of Near-Term Potential Routes and Procedures for Urban Air Mobility

Urban air mobility is gaining interest as the need for On Demand Mobility in today's congested traffic is becoming high in metropolitan areas. Urban Air Mobility (UAM) is envisioned as a concept to transport passengers and cargo safely and efficiently using innovative aircraft in the urban areas. It is expected to improve mobility for the general public, decongest road traffic, reduce transport time and reduce the strain on existing public transport networks. There exist several challenges to Urban Air Mobility (UAM) such as integration of procedures with airspace and the airport, noise levels that are acceptable to the general public, public safety, public acceptance, vehicle certification, and more. Most of the research in the United States and European skies (DLR - German Aerospace Center) related to urban areas has focused on small UAS (Unmanned Aircraft Systems) flights (NASA's UTM (UAS Traffic Management) research) and their integration with the airspace and building safe operations in densely populated areas. Previous studies on UAM have focused on fast time simulations of the routes that are separated via a separation service and network of routes. Similarly, research in Europe has focused on the approach profile for these innovative aircraft, vertiports and battery life among others. UAM as a part of the On-Demand Mobility effort has provided some guidelines for operations as shown below: Does not require additional ATC (Air Traffic Control) infrastructure; Does not impose additional workload on ATC; Does not restrict operations of traditional airspace users; Will meet appropriate safety thresholds and requirements; Will prioritize operational scalability; Will allow flexibility where possible and structure where necessary. This paper explores potential routes and procedures in a Human-In-The-Loop (HITL) experiment that could be applied in the near-term to allow integration of UAM flights into the airspace as well as a large airport. The airspace that was explored was Dallas Fort Worth (DFW) airspace managed by the DFW East Tower in South Flow only. In addition, Dallas Love Field (DAL) and Addison (ADS) airspace were also part of the testbed. The initial set of routes investigated in this study were published helicopter routes in the DFW area. Figure 1 shows class B airspace in DFW area and the origin/destination city pairs where UAM flights flew along with helicopter routes shown in blue. The research focused on exploring procedures for integrating UAM flights into Class Bravo and Class Delta airspace. Three different communication procedures, evaluated with three different levels of UAM traffic, are shown in Table 1. The current day routes were evaluated with current day communication procedures were explored as the first condition. The current day routes were also evaluated in the second condition with reduced communications, which was assumed due to the presence of a Letter Of Agreement (LOA). The purpose of the LOA was to reduce the verbiage associated with pilots getting clearance to Class B airspace from the controllers, pre-assigning beacons codes to the UAM flights, separate routes by assigning altitudes and speeds to flights going in any one direction. Flights were expected to automatically change frequency when exiting Class B airspace, thus transition points for entry and exit points were also specified in the LOA.

Urban Air Mobility↗

UAS Traffic Management (UTM) Simulation Capabilities and Laboratory Environment

NASA has engaged in collaborative research with the FAA to explore the concepts and requirements necessary to enable the safe and scalable application of small unmanned aircraft systems (UAS) in low-altitude airspace. In this effort, the UAS Traffic Management (UTM) project has developed a multi-faceted simulation component that supports near-term live flight testing in addition to further term concept exploration. This paper provides an overview of the simulation capabilities currently available as part of the UTM project and the laboratory environment in which they are applied.

Homola, Jeffrey↗

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗

A Ground-Delay-Based Approach to Reduce Impedance-Based Airspace Complexity

This paper introduces a ground-delay-based traffic management approach to reduce the impedance-based airspace complexity for a given scenario. This work extends our prior research on developing an impedance-based complexity metric for unmanned aircraft system traffic scenario classification. Impedance-based metric was evaluated for 1045 randomly generated scenarios. Scenarios with overall impedance above a certain threshold were declared as not feasible. A ground-delay-based approach was developed to be applied to the rest of the scenarios so as to remediate any scenarios with small areas of high impedance on their impedance maps. A sample application is shown for a scenario with sixty flights. The detailed trade-offs between overall accrued system delay, the number of delayed flights, the total number of conflicts and the highest impedance observed as a function of the delay tolerance for each aircraft are provided. Potential applications to Urban Air Mobility traffic scenarios are also discussed.

ground-delay based traffic management↗

Considerations in Assuring Safety of Increasingly Autonomous Systems

Recent technological advances have accelerated the development and application of increasingly autonomous (IA) systems in civil and military aviation. IA systems can provide automation of complex mission tasks-ranging across reduced crew operations, air-traffic management, and unmanned, autonomous aircraft-with most applications calling for collaboration and teaming among humans and IA agents. IA systems are expected to provide benefits in terms of safety, reliability, efficiency, affordability, and previously unattainable mission capability. There is also a potential for improving safety by removal of human errors. There are, however, several challenges in the safety assurance of these systems due to the highly adaptive and non-deterministic behavior of these systems, and vulnerabilities due to potential divergence of airplane state awareness between the IA system and humans. These systems must deal with external sensors and actuators, and they must respond in time commensurate with the activities of the system in its environment. One of the main challenges is that safety assurance, currently relying upon authority transfer from an autonomous function to a human to mitigate safety concerns, will need to address their mitigation by automation in a collaborative dynamic context. These challenges have a fundamental, multidimensional impact on the safety assurance methods, system architecture, and V&V capabilities to be employed. The goal of this report is to identify relevant issues to be addressed in these areas, the potential gaps in the current safety assurance techniques, and critical questions that would need to be answered to assure safety of IA systems. We focus on a scenario of reduced crew operation when an IA system is employed which reduces, changes or eliminates a human's role in transition from two-pilot operations.

Alves, Erin E.↗

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗

Formalized Reasoning of Operational Volumes for Wildland Fire Fighting

This work is focused on the formalized reasoning of operational volumes as it relates to the current and future technologies developed by NASA to aid in wildfire fighting operations. One such technology is the unmanned aircraft system pilot kit (UASP-kit) developed by the Scalable Traffic Management for Emergency Response Operations (STEReO) project at NASA, which is used to increase situation awareness for a ground operator in the field. The UASP-kit utilizes operational volumes which represent mission areas and alerting volumes, to alert when another aircraft is within one of these volumes from received ADS-B data. This work is focused on developing a rigorous foundation for the concept of operational volumes for modeling and prototyping operations in such a tool as the UASP-kit. This includes establishing a class of algorithms to detect when an object is in an operational volume, and when an operational volume is intersecting or contained within another. Additionally, this work is focused on providing rigorous proof in an interactive theorem prover that the algorithms work as intended. Scenarios are presented that model current UASP-kit operations and extend past the current capabilities of the technology to modeling more complex scenarios such as mission planning.

Operational Volumes↗