Results for “Air mobility” — Page 13

NASA NTRSDate not supplied

Demand Capacity Balancing at Vertiports for Urban Air Mobility

Demand Capacity Balancing (DCB) can be applied in strategic conflict management for safe Urban Air Mobility (UAM) operations. Even when the operational tempo is low, traffic demand can locally exceed the capacity at airspace resources like vertiports. This paper proposes a DCB algorithm to manage the UAM traffic demand strategically, given the capacity at vertiports. The DCB algorithm is evaluated with traffic scenarios at Dallas/Fort Worth urban area in terms of various metrics such as demand distribution changes, pre-departure delay, and the number of simultaneous operations in the air. With the same experiment setup, more extended studies are also conducted to investigate how the UAM flight scheduling based on the DCB algorithm is affected by various conditions that can occur in a practical UAM environment, including vertiport capacity changes, a slot size parameter in capacity constraint, differences in operational policy between operators like lead time for flight plan submission and cruise flight speed, and uncertainties in actual departure and arrival times.

Urban Air Mobility↗

NASA NTRSDate not supplied

Development of Urban Air Mobility (UAM) Vehicles for Ease of Operation

To date the air transportation system has been developed with the in-cremental introduction of new technology and with highly experienced air transport pilots and air traffic controllers overseeing flight operations. Thus, we currently have one of the safest commercial aviation systems in the world. General Aviation (GA) in the United States, however, has not always followed the same cautious and monitored approach to implementation; consequently, the GA safety record does not meet the high standards of commercial aviation. Recently, a new system known as Urban Air Mobility (UAM), is attracting considerable interest and investment from industry and government agencies. UAM refers to a system of passenger and small-cargo air transportation vehicles within an urban area with the goal of reducing the number of times we need to use our cars, thus improving urban traffic by moving people and cargo from crowded single pas-senger vehicles on our roads to personal and on-demand air vehicles. These UAM vehicles will be small and based on electric, Vertical-Take-Off-and-Landing (eV-TOL) systems. A significant component of UAM is offloading of flight-man-agement responsibilities from human pilots to newly-developed autonomy. Cur-rently, over 100 UAM vehicles are either in development or production. Most, if not all, have a goal of fully autonomous vehicle operations, but fully autonomous flying vehicles are not expected in the near future. Therefore, we are de-veloping concepts for UAM vehicles that will be easy to fly and/or manage by operators with minimal pilot training. In this paper we will discuss our human-automation teaming approach to develop an easy-to-operate VTOL aircraft, and some of the fly-by-wire technology needed to stabilize the vehicle so that a sim-ple ecological mental model of the flying task can be implemented. We will discuss the requirements for a stability augmentation system that must be developed to support our simple pilot input model, and also present design guidelines and requirements based on a pilot input and management model. Finally, our ap-proach to vehicle development will involve considerable operator testing and evaluation: improving pilot model, inceptors, displays and also work on a plan for how a UAM vehicle can be integrated with terminal area air traffic control airspace with minimal impact on controller workload.

UAM↗

NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

distributed sensing↗

NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

Distributed sensing↗

NASA NTRS2021

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↗

NASA NTRSDate not supplied

NASA’s MBSE Approach for Advanced Air Mobility

NASA’s Aeronautics Research Mission Directorate (ARMD) has a significant research effort for advanced air mobility (AAM). AAM involves bringing aviation closer to where people live and work and offers the possibility of making aviation a normal part of everyday life. The scope of AAM is broad, including transformations in aircraft, airspace operations, and in how these new aviation capabilities will integrate into local communities. Due to the nature of AAM cutting across multiple aspects of the aircraft, airspace, and community domains, NASA is applying tools and techniques aligned with a model-based systems engineering approach. These are intended to capture and organize applicable system architectures and potential requirements in order to deliver a validated system architecture and recommended set of requirements that enable sustainable and scalable medium density AAM operations.

Advanced Air Mobility↗

NASA NTRSDate not supplied

Design of a Six-Tiltrotor Concept Vehicle for Urban Air Mobility

NASA has developed a series of aircraft concepts known as reference vehicles for urban air mobility operations to facilitate research and development, enabling system-level comparisons between design candidates. In this study, new six-tiltrotor reference vehicles with full-electric and turboelectric propulsion systems were developed using the NASA Design and Analysis of Rotorcraft (NDARC) tool. The sizing results and performance metrics of these new vehicles are presented, along with comparisons to existing reference vehicles. The turboelectric six-tiltrotor is shown to be the fastest among the turboelectric reference vehicles. Although the full-electric six-tiltrotor is not as fast as the turboelectric version, it still offers considerable speed along with increased safety compared to the tiltrotor reference vehicle.

Six-Tiltrotor↗

NASA NTRSDate not supplied

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↗

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 NTRS2026

Introduction to the Special Issue on Advanced Air Mobility Noise: Predictions, Measurements and Perception

This Special Issue focuses on noise associated with Advanced Air Mobility (AAM), an emerging class of predominantly electric distributed-propulsion aircraft designed for urban and regional transportation. As these vehicles move toward certification and deployment, noise has become a central challenge for regulatory approval and public acceptance, particularly due to operations in densely populated areas and at low altitudes. The 24 contributions in this issue address three key aspects of AAM noise: prediction, measurement, and human perception. Prediction studies span a wide range of modeling fidelities, from high-resolution simulations to improved semi-analytical approaches, and examine complex aeroacoustic mechanisms including rotor interactions, turbulence ingestion, and broadband noise generation. Measurement studies, largely at model scale, provide new insights into tonal and broadband noise characteristics across configurations and operating conditions, while supporting model validation. Perception-focused contributions investigate annoyance, sound quality metrics, and auralization, emphasizing the role of context and operational factors in shaping human response. Together, these works highlight the interdisciplinary nature of AAM noise research and the need for integrated approaches to enable quieter vehicle design.

Perception↗

NASA NTRSDate not supplied

Conceptual Design of Tiltrotor Aircraft for Urban Air Mobility

There has been an abundance of new and novel aircraft designs created for Urban Air Mobility (UAM) in recent years. The National Aeronautics and Space Administration (NASA) contributes to the research and development of this industry in part by applying its aircraft design tools to create conceptual designs of UAM reference vehicles. The vehicles are intended to quantify the tradeoffs and performance capabilities necessary for VTOL (vertical takeoff and landing) aircraft in the UAM design space. The reference vehicles represent a variety of configurations that seek to encompass many of the design characteristics suitable for UAM. This work focuses on the conceptual design process of two new NASA reference vehicles. Both aircraft are configured as conventional tiltrotors, but one is powered by turboshaft engines, and one is fully electric. The sizing and performance of the two aircraft are discussed, as well as how the performance and characteristics compare to a selection of other NASA reference vehicles. It is found that the tiltrotor configuration is capable of reaching speeds 43% to 51% faster than the other turboshaft designs, and 54% to 93% faster than the other electric designs. The increased speed leads to a 24% to 42% decrease in overall mission time.

Conceptual Design↗

NASA NTRSDate not supplied

Advancing Electric Propulsion Aircraft Evaluation for Urban Air Mobility: Insights from NASA Ames

This presentation delves into a recent evaluation conducted at NASA-Ames on the Vertical Motion Simulator, focusing on the handling qualities of Distributed Electric Propulsion VTOL (eVTOL) aircraft, specifically tailored for Urban Air Mobility (UAM) applications. The presentation will focus on the recent effort to adapt and refine use of the Aeronautical Design Standard -33 (ADS-33) rotorcraft handling qualities developed by the U.S. Army and NASA to meet the diverse needs of civilian (eVTOL) concept evaluation. A brief discussion of the author’s personal test pilot insights in the early development of military Fly-By-Wire evaluation methods will also be provided. The emergence of innovative eVTOL designs with unique lift capabilities and flight control systems, present both opportunities and challenges, particularly in ensuring safety amidst technological complexity. To navigate these challenges, our investigation examined evaluation criteria designed to accommodate the varied configurations and advanced automation systems inherent in modern eVTOL aircraft. By establishing a standardized approach to evaluation, our research not only fosters innovation but also upholds safety standards in the dynamic landscape of urban air mobility. Through this endeavor, we help to facilitate the seamless integration of novel aircraft capabilities into new operations, contributing to a new era of safe and efficient aerial transportation.

eVTOL↗

NASA NTRSDate not supplied

Advancing Electric Propulsion Aircraft Evaluation for Urban Air Mobility: Insights from NASA-Ames

This presentation delves into a recent evaluation conducted at NASA-Ames on the Vertical Motion Simulator, focusing on the handling qualities of Distributed Electric Propulsion VTOL (eVTOL) aircraft, specifically tailored for Urban Air Mobility (UAM) applications. The presentation will focus on the recent effort to adapt and refine use of the Aeronautical Design Standard -33 (ADS-33) rotorcraft handling qualities developed by the U.S. Army and NASA to meet the diverse needs of civilian (eVTOL) concept evaluation. A brief discussion of the author’s personal test pilot insights in the early development of military Fly-By-Wire evaluation methods will also be provided. The emergence of innovative eVTOL designs with unique lift capabilities and flight control systems, present both opportunities and challenges, particularly in ensuring safety amidst technological complexity. To navigate these challenges, our investigation examined evaluation criteria designed to accommodate the varied configurations and advanced automation systems inherent in modern eVTOL aircraft. By establishing a standardized approach to evaluation, our research not only fosters innovation but also upholds safety standards in the dynamic landscape of urban air mobility. Through this endeavor, we help to facilitate the seamless integration of novel aircraft capabilities into new operations, contributing to a new era of safe and efficient aerial transportation.

Loran Allen Haworth↗

NASA NTRSDate not supplied

Demand Capacity Balancing at Vertiports for Initial Strategic Conflict Management of Urban Air Mobility Operations

Demand Capacity Balancing (DCB) can be applied in strategic conflict management for safe Urban Air Mobility (UAM) operations. Even when the operational tempo is low, traffic demand can locally exceed the capacity at airspace resources like vertiports. This paper proposes a DCB algorithm to manage the UAM traffic demand strategically, given the capacity at vertiports. The DCB algorithm is evaluated with traffic scenarios at Dallas/Fort Worth urban area in terms of various metrics such as demand distribution changes, pre-departure delay, and the number of simultaneous operations in the air. With the same experiment setup, more extended studies are also conducted to investigate how the UAM flight scheduling based on the DCB algorithm is affected by various conditions that can occur in a practical UAM environment, including vertiport capacity changes, a slot size parameter in capacity constraint, differences in operational policy between operators like lead time for flight plan submission and cruise flight speed, and uncertainties in actual departure and arrival times.

Urban Air Mobility↗

NASA NTRSDate not supplied

Assistive Detect and Avoid Technology in Urban Air Mobility Environments

The use of Assistive Detect and Avoid (Assistive DAA or ADAA) technology in Urban Air Mobility (UAM) environments poses potential benefits as well as challenges. Assistive DAA refers to the leveraged use of DAA technology, originally developed to replace see-and-avoid capabilities for remotely piloted aircraft, in onboard-piloted aircraft to augment (rather than replace) pilots’ see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be especially safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future UAM environments. ADAA may also enable higher-tempo UAM operations than with only see-and-avoid capabilities, while still maintaining acceptable levels of safety. UAM concepts under development by the FAA, NASA, and industry focus on operations moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA Langley Research Center, in collaboration with FAA researchers at the William J. Hughes Technical Center in Atlantic City, NJ, have conducted a series of medium-fidelity, human-in-the-loop research simulations of potential future UAM operations and concepts in both Class C and Class B airspace environments. These simulations have included use of a Langley-developed ADAA research tool called DANTi, which enables configurable ADAA displays to be presented to pilots of simulated eVTOL aircraft participating in higher-density and higher-tempo UAM operations. Experience and observations made during testing of the NASA-developed DANTi ADAA capability in the UAM NFLITE simulation environment will be reported in this paper together with a discussion of airspace integration and regulatory topics.

Detect and Avoid↗

NASA NTRSDate not supplied

Assistive Detect and Avoid Technology in Urban Air Mobility Environments

The use of Assistive Detect and Avoid (Assistive DAA or ADAA) technology in Urban Air Mobility (UAM) environments poses potential benefits as well as challenges. Assistive DAA refers to the leveraged use of DAA technology, originally developed to replace see-and-avoid capabilities for remotely piloted aircraft, in onboard-piloted aircraft to augment (rather than replace) pilots’ see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be especially safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future UAM environments. ADAA may also enable higher-tempo UAM operations than with only see-and-avoid capabilities, while still maintaining acceptable levels of safety. UAM concepts under development by the FAA, NASA, and industry focus on operations moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA Langley Research Center, in collaboration with FAA researchers at the William J. Hughes Technical Center in Atlantic City, NJ, have conducted a series of medium-fidelity, human-in-the-loop research simulations of potential future UAM operations and concepts in both Class C and Class B airspace environments. These simulations have included use of a Langley-developed ADAA research tool called DANTi, which enables configurable ADAA displays to be presented to pilots of simulated eVTOL aircraft participating in higher-density and higher-tempo UAM operations. Experience and observations made during testing of the NASA-developed DANTi ADAA capability in the UAM NFLITE simulation environment will be reported in this paper together with a discussion of airspace integration and regulatory topics.

Detect and Avoid↗

NASA NTRSDate not supplied

Urban Air Mobility (UAM) Vision Concept of Operations (ConOps) UAM Maturity Level (UML)-4 Overview

The Vision ConOps is intended as a foundation to engage members of the UAM community and provide a consensus on the future vision of UAM operations. It provides a concept for more detailed discussion and a basis for the exploration of ideas using a common framework to inform the continued development and integration of UAM as part of the broader transportation system. Advanced Air Mobility (AAM) encompasses a range of innovative aviation technologies (small drones, electric aircraft, automated air traffic management, etc.) that are transforming aviation’s role in everyday life, including the movement of goods and people. Urban Air Mobility (UAM) represents one of the most exciting and complex AAM concepts with highly automated aircraft, providing commercial services to the public over densely populated cities.

Brian Hill↗

NASA NTRS2019

Urban Air Mobility Fleet Manager Gap Analysis and System Design

NASA's Urban Air Mobility (UAM) Sub-Project is engaged in research to support the introduction of air taxis into the National Airspace System. Such operations will require a range of communication, navigation, and surveillance systems. Air vehicles for UAM are under development and will initially have human pilots. Separation from other aircraft, obstacles, and weather may be a pilot responsibility or provided by an operator's ground-based systems. Eventually, air taxis may be flown from the ground or fly autonomously. There will be a need for dispatch services for UAM. This report presents a gap analysis, data and capability requirements, and workstation design concepts for the UAM dispatcher or Fleet Manager (FM) position.

Mogford, Richard↗