Results for “Mobile” — Page 66

NASA NTRSDate not supplied

A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM)

The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.

In-Time Aviation Safety Management System↗

NASA NTRSDate not supplied

Multirotor Configuration Trades Informed by Handling Qualities for Urban Air Mobility Application

Many contemporary Advanced Air Mobility (AAM), and more specifically, urban air mobility (UAM) vehicle designers are attracted to variable rotor speed-controlled designs with multiple rotors because of the great potential for mass savings compared to more traditional, variable blade pitch-controlled vehicles. These designs are based on the assumption that the stability and control of recreation or basic utility-sized drones can be scaled to larger passenger-sized vehicles. Previous work had shown the challenges in stabilizing passenger-sized quadcopters. In this study, power constraints were made less restrictive and varied, allowing more control power. Motor parameters such as efficiency, nominal voltage and current operating point, and rise time of the rotor speed controller step response were studied. By fixing the efficiency of the motor to 95% and assuming a motor voltage to current ratio of 2.0 (previously, assumed to be 1.0), the authors were able to stabilize the quadcopter in the roll axis because this allowed the vehicle to achieve adequate rise times between 0.4 and 0.8 s. This motor optimization was extended to a hexacopter and octocopter designed to the same payload size and mission as the quadcopter. The three vehicle configurations and their motor speed controllers were compared. It was found that while hexacopter and octocopter required more mass and overall power; all three configurations had similar margins required for control. However, the hexacopter and octocopter were able to use this power margin to achieve lower rise times (i.e. the vehicle responded more quickly to pilot inputs) than the quadcopter, with the octocopter having the lowest rotor response rise time of the three vehicle configurations studied.

Multirotor↗

NASA NTRSDate not supplied

A Review on Cybersecurity Vulnerabilities for Urban Air Mobility

Recent developments of high-powered unmanned aerial vehicles (UAVs) have allowed for urban air mobility (UAM) to become a reality. While the propulsive technology of these flying cars has almost reached an economic level, the infrastructure to allow for these vehicles to operate in an urban environment is still lacking. With numerous known vulnerabilities in UAVs and commercial aircraft, manufacturers have not addressed cybersecurity in the scope of urban air mobility. This paper presents a review of several known cybersecurity vulnerabilities and previous attacks associated with the core communication systems of UAVs and aircraft. Analyzing current solutions to each threat and incorporating early concepts for UAM, this paper then presents a basic framework featuring a blockchain-based PKI with secondary navigation systems to allow for the development of secure airspace.

Urban Air Mobility↗

NASA NTRS2021

Description of the NASA Urban Air Mobility Maturity Level (UML) Scale

As part of its assessment of the nascent passenger-carrying urban air mobility (UAM) ecosystem, NASA’s UAM Coordination and Assessment Team developed a framework known as the UAM Maturity Level (UML) scale. This framework is intended to have multiple applications including: 1) insight into the likely operational capabilities as a UAM air transportation system develops over time; 2) analysis of technology and regulatory requirements associated with the UAM maturation process; 3) assessment of the current maturity of various segments of the UAM ecosystem; 4) coordination of UAM ecosystem priorities and areas of emphasis; and 5) increasing community and public awareness of UAM and how it may affect mobility in the future. This paper describes the structure of the UML scale and its levels. The paper also describes candidate strategies for advancing between levels, along with associated regulatory gaps and considerations.

Urban Air Mobility↗

NASA NTRSDate not supplied

Prediction-Based Auralization of a Multirotor Urban Air Mobility Vehicle

Recent advances in auralization methods applicable to rotary wing vehicles have made it possible to undertake a prediction-based auralization of a representative multirotor urban air mobility vehicle. These advances include a new capability for synthesizing loading and thickness noise directly from the prediction method and a new capability for predicting and synthesizing modulating broadband self noise within a unified system noise prediction-auralization framework. These capabilities are demonstrated for a six passenger quadrotor reference vehicle design using collective-pitch control. Propagation of the source noise to a ground observer completes the auralization process. The demonstrated capability serves as the basis for future work directed at perception-influenced design of low noise urban air mobility vehicles.

Auralization↗

NASA NTRSDate not supplied

A Review on Cybersecurity Vulnerabilities for Urban Air Mobility

Recent developments of high-powered unmanned aerial vehicles (UAVs) have allowed for urban air mobility (UAM) to become a reality. While these flying cars' propulsive technology has almost become economically viable, the infrastructure to allow these vehicles to operate in an urban environment is still lacking. With numerous known vulnerabilities in UAVs and commercial aircraft, manufacturers have not addressed cybersecurity in the scope of urban air mobility.

UAM↗

NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management for Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope prediction↗

NASA NTRSDate not supplied

A Review on Cybersecurity Vulnerabilities for Urban Air Mobility

Recent developments of high-powered unmanned aerial vehicles (UAVs) have allowed for urban air mobility (UAM) to become a reality. While these flying cars' propulsive technology has almost become economically viable, the infrastructure to allow these vehicles to operate in an urban environment is still lacking. With numerous known vulnerabilities in UAVs and commercial aircraft, manufacturers have not addressed cybersecurity in the scope of urban air mobility.

Urban Air Mobility↗

NASA NTRSDate not supplied

Minimum-Violation Traffic Management for Urban Air Mobility

Urban air mobility (UAM) refers to air transportation services in and over an urban area and has the potential to revolutionize mobility solutions. However, due to the projected scale of operations, current air traffic management (ATM) techniques are not viable. Increasingly autonomous systems are a pathway to accelerate the realization of UAM operations but must be fielded safely and efficiently. The heavily regulated, safety critical nature of aviation may lead to multiple, competing safety constraints that can be traded off based on the operational context. In this paper, we design a framework which allows for the scalable planning of a UAM ATM system. We formalize safety oriented constraints derived from FAA regulations by encoding them as temporal logic formulae. We then propose a method for UAM ATM that is both scalable and minimally violates the temporal logic constraints. Numerical results show that the runtime for our proposed algorithm is suitable for very large problems and is backed by theoretical guarantees of correctness with respect to given temporal logic constraints.

Urban Air Mobility↗

NASA NTRS2021

Noise Exposure Maps of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection

Urban Air Mobility↗

NASA NTRS2021

Noise Exposure Map of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection. (To hear the voice please utilize the video uploaded to the record)

Urban Air Mobility↗

NASA NTRSDate not supplied

The Gandalf Staff: A Mobile Tool for Lunar Exploration (2nd year of development)

The Gandalf Staff is a mobile tool designed to be a flexible device supporting crewed and uncrewed operations on the lunar surface. The core of the device is a 24v battery with communications and data storage systems. Initial optional components supporting crewed Extra-Vehicular Activity (EVA) include a LiDAR and 360˚ camera. These provide 3D mapping of the traverse for documentation, and to aid future planning. The mapping also creates outreach opportunities for the public to “stand beside” the astronaut in Virtual Reality (VR). The staff provides external lighting for field site illumination in the south polar region low sun angle environment. Navigation instruments for crew position determination with Lunar Search and Rescue (LunaSAR) are also included. The staff itself can be used as a walking aid or as a splint for Incapacitated Crew Rescue (ICR). As a stand-alone device, the staff operates as a long duration untended science platform collecting environmental data and sending it to a lunar base station. The stand-alone mode requires connection to an auxiliary power source (e.g. solar array) and energy storage system (e.g. battery), so it could become an electrical recharging station. To make rapid progress in the 1st year, and also to demonstrate innovative project management techniques, NASA guided a private industry partner, T STAR, in leading Capstone Engineering student teams at Texas A&M University (TAMU) for proof-of-concept development and testing. These teams developed the power system and demonstrated successful integration of LiDAR, WiFi communications, and external lighting subsystems. Another industry team at Jacobs Technology prototyped a tripod to hold the staff upright. For the 2nd year (FY’22), NASA will again collaborate with partners to prototype enhanced power and lighting concepts. Year 2 will also add new capability for LunaSAR and geophysical science instrumentation using a heat probe. The heat probe is based upon Apollo heritage but modified to measure subsurface volatile ice regimes at the Artemis landing site. Components of the Gandalf Staff can be developed, tested, and deployed independently, or on the integrated staff, rovers, or utility trailers. The project supports crew safety, lunar sample curation, mission science, and public outreach goals of NASA. PLAIN TEST SUMMARY: Gandalf Staff is a 24v battery powered mobile tool for the lunar surface supporting crewed geologic field site exploration, or as a stand-alone science platform. As a tool assisting astronauts conducting field geology, the Gandalf Staff provides external lighting to illuminate shadowed regions on the surface. It also documents the process of collecting rocks and dust samples using a LiDAR (laser range instrument) and cameras. The staff provides a beacon for emergency location of astronauts and augments communications when the astronauts are blocked by large boulders. As a standalone science platform, the Gandalf Staff provides a power system for instruments and sensors to measure the lunar environment over long periods of time. The staff gathers data and sends the results to a lunar base station for analysis.

External Lighting↗

NASA NTRSDate not supplied

Activities of the NASA Urban Air Mobility Noise Working Group (UNWG)

The NASA-led Urban Air Mobility Noise Working Group was established in 2018 following an exploratory meeting of stakeholders from traditional and emerging aviation sectors across industry, government agencies, academia, and community groups. Its mission is to create and support a diverse community of acoustics experts to identify, discuss, and address noise issues associated with UAM vehicles and their operations. The UNWG is comprised of four subgroups including Tools and Technologies, Ground and Flight Testing, Human Response and Metrics, and Regulation and Policy. In 2020, NASA published the white paper entitled “Urban Air Mobility Noise: Current Practice, Gaps, and Recommendations,” that presents a set of high-level goals and makes recommendations to address gaps in the current practice. This presentation is about recent activities of each of the subgroups to address those recommendations, including work towards establishment of an aeroacoustic test database for model validation, development of a set of measurement guidelines to quantify vehicle acoustic emission, a remotely administered human response study for quantifying annoyance to UAM operations, and status on noise standard, regulation, policy, and community engagement developments.

Urban air mobility↗

NASA NTRSDate not supplied

Analysis of Conflicts among Urban Air Mobility Aircraft and with Traditional Aircraft

This paper provides an initial analysis of conflicts among Urban Air Mobility aircraft and with traditional aircraft based on fast-time simulations of 20 full-day scenarios. Several sets of separation minima with added performance-based separation are applied, and the resulting separation conflicts are classified. Safety metrics relevant to separation standards are evaluated. The results shed light on future performance-based separation standards and safety metrics for separation standards involving Urban Air Mobility aircraft.

urban air mobility↗

NASA NTRSDate not supplied

Analysis of Conflicts among Urban Air Mobility Aircraft and with Traditional Aircraft

This paper provides an initial analysis of conflicts among Urban Air Mobility aircraft and with traditional aircraft based on fast-time simulations of 20 full-day scenarios. Several sets of separation minima with added performance-based separation are applied, and the resulting separation conflicts are classified. Safety metrics relevant to separation standards are evaluated. The results shed light on future performance-based separation standards and safety metrics for separation standards involving Urban Air Mobility aircraft.

urban air mobility↗

NASA NTRSDate not supplied

Foundational Human-Autonomy Teaming Research and Development in Scalable Remotely Operated Advanced Air Mobility Operations: Research Model and Initial Work

To achieve the scalability envisioned for many Advanced Air Mobility (AAM) applications, uncrewed aerial system (UAS) concepts are being pursued with the goal of enabling fewer human operators to manage more increasingly autonomous vehicles. NASA’s Transformational Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) subproject has identified human-autonomy teaming (HAT) as a critical area of research required to support these operations. Under T3-RAM, the HAT Foundational Research Activity has been tasked with providing basic research to identify HAT and human-automation interaction (HAI) principles that can be used to achieve scalable multi-vehicle UAS operations. This paper first outlines a research model to produce ecologically relevant basic research, then contextualizes completed and planned research and development activities within this model. Proposed research threads are presented, along with their practical and theoretical implications.

Human-Autonomy Teaming↗

NASA NTRS2023

An Interface Specification for Urban Air Mobility Performance Models to Support Air Traffic Management Research

Performance modeling of Urban Air Mobility vehicles in support of Air Traffic Management research poses new challenges. These aircraft often rely on a combination of fixed-wing and rotorcraft performance capabilities to enable a new and still-evolving concept of high-volume operations in densely populated areas. These characteristics lead to variability in performance model format and functionality, complicating model development and leading to difficulties for users integrating the models into their applications. This paper describes an interface specification for performance models that is intended to help address this issue. The interface aims to support the core functionality of performance models while also providing the necessary flexibility to both model developers and users. The specification describes the required model documentation, required inputs to the model, and required outputs from the model in general terms that are adaptable to most programming languages. The utilization of an appropriate interface specification will support the development of an Urban Air Mobility performance model database and help to improve interoperability of these models for a broad array of user applications.

Trajectory Prediction↗

NASA NTRS2023

An Interface Specification for Urban Air Mobility Performance Models to Support Air Traffic Management Research

Performance modeling of Urban Air Mobility vehicles in support of Air Traffic Management research poses new challenges. These aircraft often rely on a combination of fixed-wing and rotorcraft performance capabilities to enable a new and still-evolving concept of high-volume operations in densely populated areas. These characteristics lead to variability in performance model format and functionality, complicating model development and leading to difficulties for users integrating the models into their applications. This paper describes an interface specification for performance models that is intended to help address this issue. The interface aims to support the core functionality of performance models while also providing the necessary flexibility to both model developers and users. The specification describes the required model documentation, required inputs to the model, and required outputs from the model in general terms that are adaptable to most programming languages. The utilization of an appropriate interface specification will support the development of an Urban Air Mobility performance model database and help to improve interoperability of these models for a broad array of user applications.

Trajectory Prediction↗