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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

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

NASA is conducting investigations into Advanced Air Mobility (AAM) concepts, aircraft, and operations. One of the most challenging scenarios for AAM will be enabling safe routine access into densely populated urban centers. To address challenges in the urban environment, a moderately high-fidelity simulation capability is needed to investigate AAM flight operations over a regional area for the development and evaluation of autonomy technologies. This paper describes a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (10's-100's 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 accurately simulate all phases of flight. Glass cockpit displays have been developed for monitoring aircraft operation over a detailed simulated urban environment. Simulation models have been integrated to simulate air and ground-based sensors, such as radar and LIDAR. The commercial X-Plane software package is used as a rendering engine to mimic vision-based sensors (such as onboard and ground-based cameras) at various times of day and in various weather conditions over a relatively detailed graphical model of the city. The paper presents a detailed illustration of the simulation and software architecture used for traffic over this urban region. This system is enabling the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward aircraft flight test evaluation.

Keerthana Kannan↗
NASA NTRSDate not supplied

Implementation Approach for an Electrified Aircraft Concept Vehicle in a Research Flight Simulator

A flight simulation test capability for the SUbsonic Single Aft eNgine (SUSAN) Electrofan is under development. SUSAN is a regional jet transport aircraft concept that utilizes electrified propulsion to gain benefits in fuel usage, emissions, and cost. The process, which involves the integration of independently developed models and their subsequent implementation in a flight simulator, is general and can be applied to a variety of aircraft types. However, the use of electrified propulsion adds complexity beyond that of a traditional aircraft, especially with regard to the pilot interface. The way the pilot interacts with the engines will differ from current practice, and the information displayed to the pilot will necessarily include additional variables beyond what is normally displayed in a traditional cockpit.

flight simulation↗
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 NTRS2023

A Cloud Detection Neural Network for Above-Aircraft Clouds Using Airborne Cameras

We introduce a method convolutional neural networks to detect the presence of clouds in airborne camera images. We quantify the performance of this Cloud Detection Neural Network (CDNN) using human-labeled validation data where we report a 96% accuracy in detecting clouds in testing datasets for both Zenith- viewing and Forward-viewing models. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals, with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. Comparison of the CDNN with the SPN-S on time specific intervals resulted in 93% accuracy for the zenith- viewing CDNN and 84% for the forward- viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of 0.15 for the Forward CDNN and 0.07 for the Zenith CDNN. We then quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward- looking camera mounted inside the aircraft cockpit compared to the use of an All- Sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We present results from the CDNN based on airborne imagery from the NASA Aerosol Cloud Meteorology Interactions Over the Western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol and Monsoon Processes- Philippines Experiment (CAMP2Ex). For CAMP2Ex 53% of flight dates had above- aircraft cloud fraction above 50%, while for ACTIVATE 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively.

Joseph D Nied↗
NASA NTRSDate not supplied

Development of the Mod II X-57 Piloted Simulator and Flying Qualities Predictions

This paper discusses the development of the X-57 Mod II piloted simulator along with the predicted flight dynamics of the airplane. The piloted simulator models were initially based on data published by Tecnam on a P2006T airplane but were further improved upon through parameter identification of flight data as well as modeling tools such as computational fluid dynamics. In addition to having accurate flight models, a realistic cockpit was constructed to aid pilot training. From the piloted simulator, an understanding of how the airplane will behave throughout the flight envelope using established FAR and MIL standards is discussed. Using the simulation results, this paper will show that the airplane is predicted to be statically and dynamically stable as well as having Level 1 flying qualities.

Ryan Wallace↗
NASA NTRSDate not supplied

Developing a Motion-Based System for Lunar Vehicle Handling Qualities Testing

— Motion and visual cue influences are critical in any simulator system, as they impact multiple aspects of the human’s neurovestibular and visual systems. Cues of real motion proceeds to the brain before cues of visual change. It is important therefore for simulator motion cues to exist and to match those realistically with those of the real vehicle to provide transferable training of the activity for operations. The United Kingdom’s Royal Air Force Institute of Aviation Medicine (1989)[1] stated that motion platforms are the only simulation devices capable of fully stimulating the body motion sensors. They confirmed that motion platforms can impart accelerations to the whole body and therefore exercise the automatic motion feedback-loop that operators are used to. With both visual and motion cues handling the vehicle becomes more realistic. Strachan (2019)[1] confirms motion cueing from a well set-up motion platform has been found to be important especially in conditions such as night or reduced visibility where motion cues may be more relied upon. As of this writing, the only lunar rover motion simulator is housed at the General Motors (GM) Milford Proving Ground, which only simulates the motions of a traditional car. A NASA Test Team proposed to complete a motion-based simulation system for NASA’s Lunar Terrain Vehicle (LTV) which resides at Johnson Space Center’s Systems Engineering Simulator facility. This activity integrated existing fixed base simulation capabilities with a newly procured six-degree of freedom motion base platform for the design, development, evaluation, and training associated with the LTV project. This would incorporate a South Pole Lunar virtual reality simulation using Lunar Reconnaissance Orbiter 5m/pixel high-resolution imagery and Unreal 5.2 Virtual Shadow Maps, combined with a virtual reality (VR) headset, integrated within a rover cockpit on a Mikrolar Motion Platform for evaluating human performance and vehicle handling qualities for concept roving vehicle designs. The motion-based system received its Human Rating Certification on March 2023. To begin testing the new facility, a preliminary handling qualities study was conducted. The objectives were to determine if there is a correlation amongst three handling quality methods of performance for a lunar vehicle and to understand the effects of a simulated 1/6-g loads and visuals with a motion platform on the operator while in a 1-g physical environment. The capability this system provides directly benefits the NASA’s Extravehicular Activity and Human Surface Mobility Program and NASA’s Flight Operations Directorate in evaluating the driving qualities of vehicle concepts, human performance related to the operating of a lunar surface vehicle, and assessment of suit related driving impacts. It would also provide direct operational benefit by providing a first-in class and unique simulation platform for the lunar astronaut training curriculum. The empirical knowledge of rover and human performance on this scale is paramount as there is currently no other lunar surface simulator with these capabilities. The result of this study ensures a broadly applicable method of testing for shirtsleeve, unpressurized and pressurized suited rover handling qualities.

Test Track↗
NASA NTRSDate not supplied

Lunar Rover Motion-Based Simulation System

Our team developed a motion-based simulation system for lunar terrain vehicles which resides at Johnson Space Center’s Systems Engineering Simulator (SES) facility. This activity integrates existing fixed base simulation capabilities with a newly procured motion base platform for the design, development, evaluation, and training associated with lunar terrain vehicles. This incorporates a South Pole Lunar virtual reality simulation, combined with a pair of VR headsets, integrated within a rover cockpit on a motion platform for evaluating human performance and vehicle handling qualities for concept roving vehicle designs for surface mobility operations.

Motion-Based↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗
NASA NTRSDate not supplied

Development of the X-57 Mod III/IV Piloted Simulator and Discussion of the Resultant Flighting Qualities Predictions

The all-electric X-57 Mod III aircraft was designed to demonstrate wingtip propulsion drag reduction benefits on a high-aspect-ratio wing. The X-57 Mod IV aircraft was designed to expand on the Mod III version and demonstrate the benefits of distributed electric propulsion. This paper discusses the development of theall-electricX-57 Mod III and Mod IV fixed-base pilot-in-the-loop nonlinear simulator. The paper describes the model development and the simulator cockpit construction for uses such as flight training and flying qualities analysis. Results from a stability and flying qualities analysis for both Mod III and Mod IV are presented. These results predict that both Mod III and Mod IV are stable throughout their flight envelopes. Mod III is predicted to have satisfactory flying qualities while Mod IV is predicted to have areas of adequate flying qualities.

Ryan Wallace↗
NASA NTRS2025

South Pole Lunar Lighting Studies for Driving Exploration on the Lunar Surface

NASA’s Artemis lunar missions will face new exploration challenges due to inherently low sun angles in the lunar south pole region. Whereas the Apollo missions were afforded sunlight for approximately 8 to 50-degrees above the horizon, sunlight for the next lunar missions will only be 1 to 2-degrees about the horizon. With this low angle, long shadows and high contrasts of light and dark areas will be faced by the crew and remote teleop operators while exploring the lunar surface. With this in mind, NASA developed an integrated virtual Lighting and Navigation Simulation to understand these challenges. Two studies have been conducted in this Lunar South Pole environment to evaluate the effects of natural and artificial lighting on driving and navigating a lunar rover across the surface. Early NASA studies, such as this, are used to aid in developing techniques and explore concepts of operations to promote mission success and crew safety. In the Phase One development evaluation, six astronauts were teleported to ten different lighting conditions. For each location, drivers were to drive to an imaginary target approximately 200-meters straight ahead and provide subjective feedback on their ability to drive under the given lighting conditions. Phase Two, a more operational study, four astronauts and a remote operator tested five different Artemis lunar mission scenarios. Results indicated sun direction at such low angles, especially when driving a high speed, can severely impact the crew’s ability to safely drive the rover. In the up-sun situation, with the sun directly in the driver’s eyes and compounded long shadows, the consistent preference among drivers was to initiate a tacking strategy of approximately +/- 20 to 30-degrees to improve visibility. This maneuver does require more time and rover energetics. Conversely, driving down-sun required the crew to tack as well to avoid the shadow of rover blocking the terrain. Less appreciated is how the surrounding landscape is lit. Traveling into shadowed areas, especially while facing a lit terrain beyond the shadowed area, drivers enter at their own risk due to pupil contraction making artificial lights useless. Additionally, the constant transitioning between dark and light areas are mentally taxing to the crew and natural navigational references such as the stars are invisible and therefore unusable. Slope and depth magnitude are very difficult hazards to judge when approaching a shadowed crater. This naturally leads to slower driving speeds than originally anticipated. As for observing scientifically interesting features, assessing them accurately varies greatly by the lighting condition. In most cases, the task can be completed, but the strategy is to use the sun to one’s advantage. Crew workload distribution in the cockpit for driving operations was split amongst crew. The driver primarily focused attention on visual terrain (80%) but referenced displays approximately 20% of the time, while the co-pilot/navigator generally provided directional cues to the driver. These natural lighting conditions present significant challenges for safe rover operations; however, early studies having given investigators a “first-look” into understanding of how operating on the South Lunar Pole can be accomplished.

LTv↗
NASA NTRS1984

An Automated Stall-Speed Warning System

The NASA Dryden Flight Research Facility embarked upon a project with the United States Army Aviation Engineering Flight Activity (USAAEFA) to develop and test a stall-speed warning system. NASA designed and built an automated stall-speed warning system which presents both airspeed and stall speed to the pilot. The airspeed and stall speed are computed in real time by monitoring the basic aerodynamic parameters {dynamic pressure, horizontal and vertical accelerations, and pressure altitude) and other parameters (elevator and flap positions, engine torques, and fuel flow). In addition, an aural warning at predetermined stall margins is presented to the pilot through a voice synthesizer. Once the system was designed and installed in the aircraft, a flight-test program of less than 20 hr was anticipated to determine the stall-speed software coefficients. These coefficients would then be inserted in the system's software and then test flown over a period of about 10 hr for the purposes of evaluation.

Pilot↗
NASA NTRS1983

An Automated Stall-Speed Warning System

The NASA Dryden Flight Research Facility embarked upon a project with the United States Army Aviation Engineering Flight Activity (USAAEFA) to develop and test a stall-speed warning system. NASA designed and built an automated stall-speed warning system which presents both airspeed and stall speed to the pilot. The airspeed and stall speed are computed in real time by monitoring the basic aerodynamic parameters (dynamic pressure, horizontal and vertical accelerations, and pressure altitude) and other parameters (elevator and flap positions, engine torques, and fuel flow). In addition, an aural warning at predetermined stall margins is presented to the pilot through a voice synthesizer. Once the system was designed and installed in the aircraft, a flight-test program of less than 20 hr was anticipated to determine the stall-speed software coefficients. These coefficients would then be inserted in the system's software and then test flown over a period of about 10 hr for the purposes of evaluation.

Dynamic Pressure↗
NASA NTRS2004

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↗