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At least 289 records · Page 16

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↗

Varying Levels of Automation on UAS Operator Responses to Traffic Resolution Advisories in Civil Airspace

Continuing demand for the use of Unmanned Aircraft Systems (UAS) has put increasing pressure on operations in civil airspace. The need to fly UAS in the National Airspace System (NAS) in order to perform missions vital to national security and defense, emergency management, and science is increasing at a rapid pace. In order to ensure safe operations in the NAS, operators of unmanned aircraft, like those of manned aircraft, may be required to maintain separation assurance and avoid loss of separation with other aircraft while performing their mission tasks. This experiment investigated the effects of varying levels of automation on UAS operator performance and workload while responding to conflict resolution instructions provided by the Tactical Collision Avoidance System II (TCAS II) during a UAS mission in high-density airspace. The purpose of this study was not to investigate the safety of using TCAS II on UAS, but rather to examine the effect of automation on the ability of operators to respond to traffic collision alerts. Six licensed pilots were recruited to act as UAS operators for this study. Operators were instructed to follow a specified mission flight path, while maintaining radio contact with Air Traffic Control and responding to TCAS II resolution advisories. Operators flew four, 45 minute, experimental missions with four different levels of automation: Manual, Knobs, Management by Exception, and Fully Automated. All missions included TCAS II Resolution Advisories (RAs) that required operator attention and rerouting. Operator compliance and reaction time to RAs was measured, and post-run NASA-TLX ratings were collected to measure workload. Results showed significantly higher compliance rates, faster responses to TCAS II alerts, as well as less preemptive operator actions when higher levels of automation are implemented. Physical and Temporal ratings of workload were significantly higher in the Manual condition than in the Management by Exception and Fully Automated conditions.

Kenny, Caitlin↗

Effectiveness of Redundant Communications Systems in Maintaining Operational Control of Small Unmanned Aircraft

NASA has been researching prototype technologies for an Unmanned Aircraft System (UAS) Traffic Management (UTM) system to facilitate enabling of safe and efficient civilian low-altitude airspace and UAS operations, in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for beyond visual line-of-sight (BVLOS) operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 will build on the earlier TCLs and focus on technologies and requirements for operations in higher-density urban areas for tasks such as news gathering, package delivery and for managing large-scale contingencies. This paper describes a communications test conducted in TCL3 and discusses insights gained from the test. In the test, operators were directed to equip UAS with redundant Command and Control (C2) communications systems, send a maneuver command to Unmanned Aircraft (UA) via the primary system, then verify execution of the sent command. This exercise was repeated with each redundant system. The test was designed to assess effectiveness of redundant C2 systems in maintaining operational control of UA. Several UAS were configured with varying arrangements to achieve redundancy, including two identical radio modems using the same frequency band, WiFi and Long-Term Evolution (LTE) cellular modems, etc. From the test, digital data such as time maneuver command sent, time maneuver verified, etc., were collected. Descriptions of methods to detect loss of C2 communications and contingency steps for such event were collected and assessed. The final paper will include a detailed analysis of the collected data leading to the following insights. First, effectiveness of redundant C2 systems depends on several factors, such as operational environment and communications service availability. For example, use of two identical point-to-point radio to connect operator and UA on the same frequency band can be effective in mitigating radio malfunction when operating in an environment where possibility of Radio Frequency (RF) interference is low, such as over open plains. However, the same arrangement may not be effective where high level of RF transmissions in broad spectrum ranges can be expected, such as over or near urban areas. For redundant systems that consist of external communications services, such as cellular and satellite communications network, redundancy is maintained only in the areas where more than one services are available. Therefore, UAS operators should have the means to plan for and monitor the performance of external communications services they are relying on to control UA. Second, communications performance needs, such as the minimum data transfer rate and the maximum tolerable latency, should be assessed to reflect the potential hazard that can come from loss of UA control. For example, UA operations over desolate area pose less hazard to people than operations over densely populated area and performance need for the former would be less than the latter.

Jung, Jaewoo↗

Urban Air Mobility (UAM) Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5% of the total available market, or $2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized. The barriers and challenges we characterized in this study can be stratified according to their applicability or potential mitigation through technology as well as market maturity (Figure 1). In the near term, high cost of service will be a key economic challenge. We found potential for significant reduction in service cost through increased vehicle and component efficiency, and automation in a more mature market scenario. Weather conditions also pose a challenge to the UAM market, though there is potential for mitigation of some of these impacts through technology such as sensors enabling operations in low visibility. However, even in a mature market with advanced technology, disruptions are still likely to occur due to weather events such as thunderstorms and strong winds. High density operations will likely stress the current Air Traffic Management (ATM) system in the near term, but technology and new initiatives such as the Air Traffic Management -eXploration project (ATM-X) will enable safe and efficient integration of UAM into the National Airspace System (NAS). Current battery technology creates a barrier in the near term, especially for the Air Ambulance market, as battery weight and extensive recharging times would be needed for these operations. Advancements in battery technology, as well as use of hybrid VTOLs, could significantly reduce this barrier in the longer term. As UAM emerges as a viable mode of transportation in the near term, adverse energy and environmental impacts, particularly noise, may impact community acceptance and potentially persist as the market matures into larger-scale operations. For non-technology related challenges, we found that infrastructure constraints will create a significant barrier to UAM in the near term but could be addressed in the longer term through development and expansion of vertiports. Competition from existing modes of transportation such as ride-sharing (e.g., Lyft, Uber) and ground taxi’s pose a key barrier to UAM in the short term, which will likely evolve into competition from other emerging technologies such as autonomous cars and electric trains in the longer term. Weather events will influence other components of the operation such as passenger comfort (e.g., extreme temperatures, turbulence) and infrastructure (e.g., winter weather causing cracks and degradation in vertiports). There is also potential for these impacts to be heightened in the longer term from the increased frequency of adverse weather such as thunderstorms due to changing climatic conditions. We also found that the public has strong concerns about safety as a passenger in a piloted UAM, including “lasing” of pilots, unruly passengers, and sabotage. They would prefer that all passengers pass through a security screening process before boarding a vehicle. They would also prefer to use UAM for longer regional trips, such as flying from Washington, DC to Baltimore, MD or San Diego, CA to Los Angeles, CA. A longer term automated UAM vehicle market will face challenges due to public apprehension about automation and unmanned operations, and a preference to fly with passengers they know in an autonomous (unmanned) operational scenario.

Rohit Goyal↗

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↗

Data Mining for Understanding and Improving Decision-making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions.

Weather↗

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

data mining↗

Avionics systems in the management of air transportation

Aspects of aircraft operating systems technology are discussed along with the requirements of the National Airspace System and the system requirements for transport and light aircraft. Attention is given to problems regarding man's role as systems become increasingly complex. It is pointed out that science does not know enough concerning the operation of the human body to provide information for an optimal exploitation of man's unique capabilities as manager of his aircraft.

Berkstresser, B. K.↗

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Overview for RTCA SC-228

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project started in 2021 under NASA’s Air Traffic Management – eXploration (ATM-X) project. ATM-X as a project is conducting research to support the growth of traditional aviation and new entrants. This presentation discusses the background of the PAAV project as well as it’s current areas of focus around uncrewed aircraft system (UAS) operations. The areas include the development of a flight test ecosystem, detect and avoid, traffic pattern integration, aircraft-to-aircraft communications, and contingency management. The aim of these research areas is to help inform the development of performance standards and FAA-approved procedures for integrating UAS into the national airspace system (NAS). The presentation seeks to describe the PAAV research objectives in sufficient detail to allow the committee to provide feedback on the sub-project's approach and main areas of interest.

uncrewed aircraft systems↗

Collaborative Arrival Planning: Data Sharing and User Preference Tools

Air traffic growth and air carrier economic pressures have motivated efforts to increase the flexibility of the air traffic management process and change the relationship between the air traffic control service provider and the system user. One of the most visible of these efforts is the U.S. government/industry "free flight" initiative, in which the service provider concentrates on safety and cross-airline fairness, and the user on their business objectives and operating preferences, including selecting their own path and speed in real-time. In the terminal arrival phase of flight, severe restrictions and rigid control are currently placed on system users, typically without regard for individual user operational preferences. Airborne delays applied to arriving aircraft into capacity constrained airports are imposed on a first-come, first-serve basis, and thus do not allow the system user to plan for or prioritize late arrivals, or to economically optimize their arrival sequence. A central tenant of the free-flight operating paradigm is collaboration between service providers and users in reaching air traffic management decisions. Such collaboration would be particularly beneficial to an airline's "hub" operation, where off-schedule arrival aircraft are a consistent problem, as they cause serious air-port ramp difficulties, rippling airline scheduling effects, and result in large economic inefficiencies. Greater collaboration can also lead to increased airport capacity and decrease the severity of over-capacity rush periods. In the NASA Collaborative Arrival Planning (CAP) project, both independent exchange of real-time data between the service provider and system user and collaborative decision support tools are addressed. Data exchange of real-time arrival scheduling, airspace management, and air carrier fleet data between the FAA service provider and an air carrier is being conducted and evaluated. Collaborative arrival decision support tools to allow intra-airline arrival preferences are being developed and simulated. The CAP project is part of and leveraged from the NASA/FAA Center TRACON Automation System (CTAS), a fielded set of decision support tools that provide computer generated advisories for both enroute and terminal area controllers to manage and control arrival traffic more efficiently. In this paper, the NASA Collaborative Arrival Planning project is outlined and recent results detailed, including the real-time use of CTAS arrival scheduling data by a major air carrier and simulations of tactical and strategic user preference decision support tools.

Zelenka, Richard E.↗

Preliminary Investigation of Impact of Technological Impairment on Trajectory-Based Operations

The Next Generation Air Transportation System (NextGen) incorporates collaborative air traffic management and Trajectory-Based Operations (TBO) in order to significantly increase the capacity, efficiency, and predictability of operations in the National Airspace System (NAS), without decreasing safety. This is enabled by airspace users and service providers sharing knowledge about operations that allows prediction of the complete 4D flight trajectory with as little uncertainty as possible. Additionally, new software and hardware technology is critical to reaching NextGen goals, especially with regard to TBO. What if the technologies that are critical for TBO were to be impaired or fail completely? Should there be a malfunction of a piece of the technology, it must be ensured that the whole system does not break down completely or suffer severe impairment. Instead, operations need to be maintained proportionally to the problem and safety needs to be ensured (graceful degradation). This paper proposes a systematic framework to investigate the vulnerability of TBO to technology disruption, and determine the impact of technological impairment on TBO. Two representative technologies are chosen for detailed investigation and the impact of their impairment on the degradation of TBO is illustrated using a weather-related scenario. XXXX There are several possible directions of future work. We believe it is desirable to develop methods to quantitatively assess the impact of technological disruption on TBO and to have the simulation tools to validate the impact. The availability of prognostics and health management methods could be leveraged to predict technological failure/disruption, thus predicting how TBO will be a ected, and possibly pro-actively mitigating the impact. It is important to develop large-scale scenarios where the e ect of technological impairment is prominent, and identify methods to quantitatively assess the extent of TBO degradation. An important goal of such an investigation is the development of failure-resistant resilient trajectory-based oper- ations. Resilience14, 15 is the property of a system to \bounce back" and resume at least a signi cant portion of its functionalities after degradation due to technological impairment(s). A systems resilience includes properties such as \bu ering capacity" (quantifying disruptions the system can absorb or adapt to without a fundamental breakdown in performance or in the systems structure), \ exibility" (ability to restructure itself in response to external changes or pressures), "margin" (how closely the system is currently operating rela- tive to one or another kind of performance boundary), \tolerance" (whether the system gracefully degrades as stress/pressure increase, or collapses quickly when pressure exceeds adaptive capacity), etc. Future work needs to focus on quantifying and improving the resilience of TBO, and identifying resilient design solutions for aviation.

TBO↗

MESA: Message-Based System Analysis Using Runtime Verification

In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.

Message-based System↗

Small Aircraft Transportation System Concept and Technologies

This paper summarizes both the vision and the early public-private collaborative research for the Small Aircraft Transportation System (SATS). The paper outlines an operational definition of SATS, describes how SATS conceptually differs from current air transportation capabilities, introduces four SATS operating capabilities, and explains the relation between the SATS operating capabilities and the potential for expanded air mobility. The SATS technology roadmap encompasses on-demand, widely distributed, point-to-point air mobility, through hired-pilot modes in the nearer-term, and through self-operated user modes in the farther-term. The nearer-term concept is based on aircraft and airspace technologies being developed to make the use of smaller, more widely distributed community reliever and general aviation airports and their runways more useful in more weather conditions, in commercial hired-pilot service modes. The farther-term vision is based on technical concepts that could be developed to simplify or automate many of the operational functions in the aircraft and the airspace for meeting future public transportation needs, in personally operated modes. NASA technology strategies form a roadmap between the nearer-term concept and the farther-term vision. This paper outlines a roadmap for scalable, on-demand, distributed air mobility technologies for vehicle and airspace systems. The audiences for the paper include General Aviation manufacturers, small aircraft transportation service providers, the flight training industry, airport and transportation authorities at the Federal, state and local levels, and organizations involved in planning for future National Airspace System advancements.

Small aircraft transportation system↗

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.↗

UAS Service Supplier Checkout: How UTM Confirmed Readiness of Flight Tests with UAS Service Suppliers

NASA collaborated with industry partners to develop and test the small Unmanned Aircraft System (sUAS) Traffic Management (UTM) research platform, a software prototype used for developing airspace integration requirements for sUAS operations. The lessons learned from these activities will help inform the Federal Aviation Administration (FAA) on what is needed to safely manage sUAS operations. A core component of the UTM platform is the UAS Service Supplier (USS), which acts as a communications bridge to meet the regulatory and operational requirements. As the UTM partners began USS flight tests, NASA found that it was difficult to get all USSs functioning at comparable quality levels to ensure successful flight tests. Also, NASA anticipated that the FAA would encounter similar challenges when they begin to register USSs for operational use. These realizations led to the development of USS Checkout, a set of processes and tools designed to increase flight test efficiency. We learned that a good USS Checkout process is balanced for simplicity versus test coverage, and is amenable to automation. We also learned that when USS Checkout is a USS prerequisite for flight tests, flight tests were more efficient and effective.

Smith, Irene Skupniewicz↗

A Data & Reasoning Fabric to Enable Advanced Air Mobility

A Data & Reasoning Fabric (DRF) is envisioned to enable the full potential of advanced air mobility by providing all data and reasoning where they are needed. The DRF marketplace is based on an open foundational ecosystem of data and reasoning exchange between the many systems that must seamlessly interplay to manage the envisioned highly complex and dense airspace operations. DRF activities will identify, test and - as needed - research and develop critical core technologies, and collaboratively test these technologies, open standards and architectures, and the integrated framework with end-users so as to deliver reference designs and development environments that catalyze broad private and public sector buy-in and self-sustaining development of it and associated standards.

Urban Air Mobility↗

Data and Reasoning Fabric (DRF) Phase I & Phase II Report

A Data & Reasoning Fabric (DRF) is envisioned to enable the full potential of advanced air mobility by providing all data and reasoning where they are needed. The DRF marketplace is based on an open foundational ecosystem of data and reasoning exchange between the many systems that must seamlessly interplay to manage the envisioned highly complex and dense airspace operations. DRF activities will identify, test and - as needed - research and develop critical core technologies, and collaboratively test these technologies, open standards and architectures, and the integrated framework with end-users so as to deliver reference designs and development environments that catalyze broad private and public sector buy-in and self-sustaining development of it and associated standards.

UAM↗

A Data & Reasoning Fabric to Enable Advanced Air Mobility

A Data & Reasoning Fabric (DRF) is envisioned to enable the full potential of advanced air mobility by providing all data and reasoning where they are needed. The DRF marketplace is based on an open foundational ecosystem of data and reasoning exchange between the many systems that must seamlessly interplay to manage the envisioned highly complex and dense airspace operations. DRF activities will identify, test and - as needed - research and develop critical core technologies, and collaboratively test these technologies, open standards and architectures, and the integrated framework with end-users so as to deliver reference designs and development environments that catalyze broad private and public sector buy-in and self-sustaining development of it and associated standards.

Urban Air Mobility↗