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NASA NTRS2019

Challenges in Vehicle Safety and Occupant Protection for Autonomous Electric Vertical Take-Off and Landing (eVTOL) Vehicles

The burgeoning electric Vertical Take-off and Landing (eVTOL) vehicle industry has generated a significant level of enthusiasm amongst aviation designers, manufacturers and researchers. This industry is determined to change the urban transportation paradigm from traditional ground-based vehicles (cars, taxis, buses) to air-based eVTOL vehicles which can be summoned, much like how conventional taxi services work currently. These new eVTOL vehicles are designed to be small and lightweight and operate autonomously without user intervention. There are many unknowns as to how the industry will mature. The logistics of creating a completely new category of vehicle along with its own set of rules are complex, and there are many known - and unknown - barriers to overcome. Some (of many) known barriers include airspace management, ground logistics, physical space, and, the vehicle design itself. There are many eVTOL vehicle manufacturers and organizations working these problems presently. This report will focus on one major barrier: the level of safety as it pertains to the framework of eVTOL vehicles. A high level of safety is necessary for the vehicles to gain acceptance as the public adapts to these autonomous ride-sharing services. An overview of current levels of transportation safety and some extrapolation into how eVTOL vehicles might compare is first presented. Next, a discussion categorizing the major differences between Crash Prevention and Crash Mitigation as it pertains to eVTOL vehicle safety is included with identification of current deficiencies. The report then expands into a framework for specific ideas that could use Crash Mitigation to improve vehicle safety through a crashworthy systems level approach with several designs highlighted. Finally, a brief discussion into the regulatory approach and potential guidelines as they pertain to new eVTOL vehicles is presented. Accordingly, much of the supplemental data will be taken from sources pertaining to either General Aviation (GA) aircraft, rotorcraft, or transport category aircraft, due to the lack of overarching data from eVTOL vehicles. As of this writing, the European Aviation Safety Agency has released a draft version of a VTOL Special Condition, with a comment period closing in late 2018. It is assumed that eventual expected operations and anticipated future regulations for VTOL vehicles will consist of some combination of these (and other) sources.

Littell, Justin D.↗

NASA NTRSDate not supplied

Examining the Changing Roles and Responsibilities of Humans in Envisioned Future In-Time Aviation Safety Management Systems

Advances in technology are enabling new concepts of operations that will trans-form aviation including increasingly autonomous capabilities to handle evolving complex dynamic ecosystems like those associated with Advanced Aerial Mobility. A major challenge is how to ensure today’s safety levels are maintained as the system scales for rapid detection and timely mitigation of safety issues. NASA has developed a concept of operation for In-Time Aviation Safety Management Systems (IASMS) that represents a system-of-system perspective on interconnected capabilities needed to proactively reduce risk in complex operational environments where unknown hazards may exist. As a result, NASA research priorities include under-standing how the balance between humans and automation changes in such envisioned systems, which may lead to novel human-machine interaction paradigms and human-autonomy teaming for informed contingency management.

Lawrence Prinzel↗

NASA NTRS2012

Integrating High-Resolution Taskable Imagery into a Sensorweb for Automatic Space-Based Monitoring of Flooding in Thailand

Several space-based assets (Terra, Aqua, Earth Observing One) have been integrated into a sensorweb to monitor flooding in Thailand. In this approach, the Moderate Imaging Spectrometer (MODIS) data from Terra and Aqua is used to perform broad-scale monitoring to track flooding at the regional level (250m/pixel) and EO-1 is autonomously tasked in response to alerts to acquire higher resolution (30m/pixel) Advanced Land Imager (ALI) data. This data is then automatically processed to derive products such as surface water extent and volumetric water estimates. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. More recently, this sensorweb structure has been used to request imagery, access imagery, and process high-resolution (several m to 30m), targetable asset imagery from commercial assets including Worldview-2, Ikonos, Radarsat-2, Landsat-7, and Geo-Eye-1. We describe the overall sensorweb framework as well as new workflows and products made possible via these extensions.

sensorweb operations↗

NASA NTRS2008

G-Guidance Interface Design for Small Body Mission Simulation

The G-Guidance software implements a guidance and control (G and C) algorithm for small-body, autonomous proximity operations, developed under the Small Body GN and C task at JPL. The software is written in Matlab and interfaces with G-OPT, a JPL-developed optimization package written in C that provides G-Guidance with guaranteed convergence to a solution in a finite computation time with a prescribed accuracy. The resulting program is computationally efficient and is a prototype of an onboard, real-time algorithm for autonomous guidance and control. Two thruster firing schemes are available in G-Guidance, allowing tailoring of the software for specific mission maneuvers. For example, descent, landing, or rendezvous benefit from a thruster firing at the maneuver termination to mitigate velocity errors. Conversely, ascent or separation maneuvers benefit from an immediate firing to avoid potential drift toward a second body. The guidance portion of this software explicitly enforces user-defined control constraints and thruster silence times while minimizing total fuel usage. This program is currently specialized to small-body proximity operations, but the underlying method can be generalized to other applications.

Acikmese, Behcet↗

NASA NTRSDate not supplied

Zero-Trust Architecture for Autonomous Edge Computing

We are at the apex of an aviation revolution where autonomy will play a central role in enabling complex, multi-agent systems to communicate, interact, and collaborate on a myriad of applications spanning autonomous swarms to wild-fire management. Autonomy is not an absolute but rather a spectrum ranging from a system requiring significant human intervention to one requiring little to none [1]. For example, the extreme, in the case of an autonomous aircraft, is one that operates independently in the airspace interacting with all other elements (air traffic controllers, other pilots) as if it were a human pilot. Critical to this vision is an architecture that enables autonomous agents to interact with minimal latency. Edge computing is an emerging architecture where compute and storage is pushed to the ‘edge’ of the network in order to minimize the round-trip time from agent to resource thereby mitigating the latency associated with cloud-only based approaches. Additionally, services can generate massive amounts of data (e.g., video feeds), which may require analysis in near real-time. Moving this data to the cloud for further processing may not be feasible due to latency, bandwidth, and cost. Privacy, security, and reliability can also be improved by edge computing architectures. However, this geo-distributed and dynamic* architecture complicates the establishment of unambiguous network security boundaries and can lead to vulnerabilities including man in the middle attacks, replay attacks, physical security breaches of edge nodes, signal interception, etc. This motivates the need for zero-trust architectures [2–4] which de-emphasize the notion of static network perimeters and, as the name implies, do not instill any innate trust in any particular agent. It is required that all agents must be authorized and approved in every transaction. In this paper, we present a zero-trust architecture suitable for edge-computing applications that demand significant low-latency, security, privacy, and reliability.

zero trust↗

NASA NTRS2004

Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration

Concepts are being investigated for exploratory missions to Mars based on Bioinspired Engineering of Exploration Systems (BEES), which is a guiding principle of this effort to develop biomorphic explorers. The novelty lies in the use of a robust telecom architecture for mission data return, utilizing multiple local relays (including the lander itself as a local relay and the explorers in the dual role of a local relay) to enable ranges ~10 to 1,000 km and downlink of color imagery. As illustrated in Figure 1, multiple microflyers that can be both surface or aerially launched are envisioned in shepherding, metamorphic, and imaging roles. These microflyers imbibe key bio-inspired principles in their flight control, navigation, and visual search operations. Honey-bee inspired algorithms utilizing visual cues to perform autonomous navigation operations such as terrain following will be utilized. The instrument suite will consist of a panoramic imager and polarization imager specifically optimized to detect ice and water. For microflyers, particularly at small sizes, bio-inspired solutions appear to offer better alternate solutions than conventional engineered approaches. This investigation addresses a wide range of interrelated issues, including desired scientific data, sizes, rates, and communication ranges that can be accomplished in alternative mission scenarios. The mission illustrated in Figure 1 offers the most robust telecom architecture and the longest range for exploration with two landers being available as main local relays in addition to an ephemeral aerial probe local relay. The shepherding or metamorphic plane are in their dual role as local relays and image data collection/storage nodes. Appropriate placement of the landing site for the scout lander with respect to the main mission lander can allow coverage of extremely large ranges and enable exhaustive survey of the area of interest. In particular, this mission could help with the path planning and risk mitigation in the traverse of the long-distance surface explorer/rover. The basic requirements of design and operation of BEES to implement the scenarios are discussed. Terrestrial applications of such concepts include distributed aerial/surface measurements of meteorological events, i.e., storm watch, seismic monitoring, reconnaissance, biological chemical sensing, search and rescue, surveillance, autonomous security/ protection agents, and/or delivery and lateral distribution of agents (sensors, surface/subsurface crawlers, clean-up agents). Figure 2 illustrates an Earth demonstration that is in development, and its implementation will illustrate the value of these biomorphic mission concepts.

Thakoor, Sarita↗

NASA NTRS2009

Design for an 8 Meter Monolithic UV/OIR Space Telescope

ATLAST-8 is an 8-meter monolithic UV/optical/NIR space observatory to be placed in orbit at Sun-Earth L2 by NASA's planned Ares V cargo launch vehicle. The ATLAST-8 will yield fundamental astronomical breakthroughs. The mission concept utilizes two enabling technologies: planned Ares-V launch vehicle (scheduled for 2019) and autonomous rendezvous and docking (AR&D). The unprecedented Ares-V payload and mass capacity enables the use of a massive, monolithic, thin-meniscus primary mirror - similar to a VLT or Subaru. Furthermore, it enables simple robust design rules to mitigate cost, schedule and performance risk. AR&D enables on-orbit servicing, extending mission life and enhancing science return.

Stahl, H. Philip↗

NASA NTRS2022

A Framework for Dynamic Architecture and Functional Allocations for Increasing Airspace Autonomy

To enable scalability of air travel for use cases such as cargo delivery, it is anticipated that future air traffic operations will involve unmanned aircraft operated by remote pilots. Of particular interest are schemes where a small number of pilots operate a large number of vehicles, mitigating high cost and pilot shortage issues. Such architectures require increased levels of automation and supervisory control modes. They also require ensuring safe operations when the command and control link to the vehicle is degraded or lost completely, rendering the vehicle autonomous. To evaluate these variable and dynamic architectures, this paper will present a framework for decomposing the functions necessary to ensure safe, orderly, and expeditious air travel, assessing the agents in the system, and classifying the levels of autonomy. Then, an example allocation to agents of roles for the function of separation assurance is presented, highlighting the dependency of the allocation on three main factors: time criticality of a potential separation violation, the ratio of pilots to vehicles, and the loss of the command and control link.

air traffic management, function allocation, auton↗

NASA NTRS2022

A Framework for Dynamic Architecture and Functional Allocations for Increasing Airspace Autonomy

To enable scalability of air travel for use cases such as cargo delivery, it is anticipated that future air traffic operations will involve unmanned aircraft operated by remote pilots. Of particular interest are schemes where a small number of pilots operate a large number of vehicles, mitigating high cost and pilot shortage issues. Such architectures require increased levels of automation and supervisory control modes. They also require ensuring safe operations when the command and control link to the vehicle is degraded or lost completely, rendering the vehicle autonomous. To evaluate these variable and dynamic architectures, this paper will present a framework for decomposing the functions necessary to ensure safe, orderly, and expeditious air travel, assessing the agents in the system, and classifying the levels of autonomy. Then, an example allocation to agents of roles for the function of separation assurance is presented, highlighting the dependency of the allocation on three main factors; time criticality of a potential separation violation, the ratio of pilots to vehicles, and the loss of the command and control link.

air traffic management↗

NASA NTRSDate not supplied

Lessons Learned from Astrobee Operations on the International Space Station

Since its launch in 2019, NASA has been operating three Astrobee free-flying robots providing an autonomous and adaptable research platform aboard the International Space Station (ISS). These robots have not only facilitated a myriad of national and international research endeavors in microgravity but have also served as a STEM outreach platform for student competitions aboard the ISS. Amidst its extensive operational tenure, spanning over five years and exceeding 1200 hours of cumulative free-flyer operation as of April 2024, the Astrobee robots have encountered software and hardware anomalies. Despite its inherent design for on-orbit repair or replacement, certain anomalies have proven to be complex, necessitating remote resolution via software and firmware updates or, in extreme cases, hardware replacements or the return of faulty units to NASA's ground facilities for repair. Such challenges underscore the delicate balance between the autonomous functionality of Astrobee and the occasional need for human intervention to maintain optimal performance. One recurring point of failure identified during Astrobee's operational lifespan has been the SD card, a critical component utilized by the different Astrobee processors and the Dock Station. The occurrence of SD card anomalies, both on orbit and within ground units, has provided invaluable insights into the improvement of Astrobee's systems and mitigation to future faults. This presentation will focus on four key areas: 1. Overview of Faults and Anomalies: A comprehensive examination of the diverse array of faults and anomalies encountered by Astrobee and its associated systems both in orbit and on the ground. From software glitches to hardware malfunctions, this section provides insights into the challenges faced during Astrobee's operational tenure. 2. Resolution Processes and Procedures: An in-depth discussion of the methodologies and procedures implemented to resolve the encountered anomalies. This includes remote troubleshooting, software patches, firmware updates, and, when necessary, the logistics involved in hardware replacements or down-massing for repair. 3. Implementation of Software Updates and Hardware Upgrades: A detailed exploration of the strategies employed to mitigate the risk of recurring anomalies through the implementation of software updates and hardware upgrades. This section highlights the iterative nature of Astrobee's development, emphasizing the continuous pursuit of robustness and reliability. 4. Lessons Learned and Future Directions: Reflecting on the insights gained from addressing anomalies, this section examines the lessons learned and outlines future directions for enhancing Astrobee's robustness and resilience. It underscores the iterative nature of space exploration and the importance of adaptability and continuous improvement in the pursuit of scientific discovery. Through a nuanced examination of Astrobee's operational challenges and the strategies employed to overcome them, this presentation sheds light on the complexities of operating autonomous robotic systems in the ISS environment. It underscores NASA's commitment to pushing the boundaries of exploration and innovation while navigating the inherent challenges of space exploration.

Astrobee↗

NASA NTRSDate not supplied

Lessons Learned from Astrobee Operations on the International Space Station

Astrobee↗

NASA NTRS2024

High Density Vertiplex - Scalable Autonomous Operations - Flight Test Report

This Technical Memorandum describes the approach taken within the High Density Vertiplex Project to perform rapid prototyping and assessment of the UAM Ecosystem including representative: Onboard Autonomous Systems, Ground Control and Fleet Management Systems, Airspace Management Systems, and Vertiport Automation Systems (VAS). Small Uncrewed Aerial Systems (sUAS) were employed as effective low risk and inexpensive surrogates for larger proposed UAM aircraft to accelerate the prototyping effort, ensure safety, greatly mitigate costs, and accelerate progress. Flight testing performed included multivehicle operations where usability Human Factors (HF) data was collected on the operators.

Jacob Schaefer↗

NASA NTRS2024

A Survey of Modeling Activities by NASA’s Orbital Debris Program Office

NASA’s Orbital Debris Program Office (ODPO) develops and maintains a number of modeling tools to analyze and simulate the orbital debris environment. One of the most important products produced by the NASA ODPO is the Orbital Debris Engineering Model (ORDEM). This model can be used by satellite designers and operators to design missions for better protection against the debris environment. The ODPO is currently working on the next generation, designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and the ability to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. A new addition will be a parameterized debris shape model based on laboratory hypervelocity impact tests, including DebriSat. ORDEM is primarily based on dedicated debris measurements, such as by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, and observations of geosynchronous orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). In addition to ORDEM, the ODPO also maintains other models, such as the LEO-to-GEO Environment Debris (LEGEND) model for studies of long-term evolution of Earth’s debris environment, with the ability to study various mitigation and remediation strategies. Another model, the Satellite Breakup Risk Assessment Model (SBRAM), is used to analyze how satellite breakups may affect critical space missions (such as the ISS) on short notice. In addition to these models, the ODPO maintains other secondary models used to model satellite explosions and collisions, analyze radar, optical, and in situ data, and to model such things as solar activity and orbit evolution. In this presentation, a survey of these models will be presented, showing how the different models are used together to create a comprehensive picture of Earth’s debris environment.

Mark Matney↗

NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗

NASA NTRS1984

Autonomous Integrated Receive System (AIRS) requirements definition. Volume 2: Design and development

Functional requirements and specifications are defined for an autonomous integrated receive system (AIRS) to be used as an improvement in the current tracking and data relay satellite system (TDRSS), and as a receiving system in the future tracking and data acquisition system (TDAS). The AIRS provides improved acquisition, tracking, bit error rate (BER), RFI mitigation techniques, and data operations performance compared to the current TDRSS ground segment receive system. A computer model of the AIRS is used to provide simulation results predicting the performance of AIRS. Cost and technology assessments are included.

Chie, C. M.↗

NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗

NASA NTRS2016

Conceptual Drivers for an Exploration Medical System

Interplanetary spaceflight, such as NASA's proposed three-year mission to Mars, provides unique and novel challenges when compared with human spaceflight to date. Extended distance and multi-year missions introduce new elements of operational complexity and additional risk. These elements include: inability to resupply medications and consumables, inability to evacuate injured or ill crew, uncharted psychosocial conditions, and communication delays that create a requirement for some level of autonomous medical capability. Because of these unique challenges, the approaches used in prior programs have limited application to a Mars mission. On a Mars mission, resource limitations will significantly constrain available medical capabilities, and require a paradigm shift in the approach to medical system design and risk mitigation for crew health. To respond to this need for a new paradigm, the Exploration Medical Capability (ExMC) Element is assessing each Mars mission phase-transit, surface stay, rendezvous, extravehicular activity, and return-to identify and prioritize medical needs for the journey beyond low Earth orbit (LEO). ExMC is addressing both planned medical operations, and unplanned contingency medical operations that meld clinical needs and research needs into a single system. This assessment is being used to derive a gap analysis and studies to support meaningful medical capabilities trades. These trades, in turn, allow the exploration medical system design to proceed from both a mission centric and ethics-based approach, and to manage the risks associated with the medical limitations inherent in an exploration class mission. This paper outlines the conceptual drivers used to derive medical system and vehicle needs from an integrated vision of how medical care will be provided within this paradigm. Keywords: (Max 6 keywords: exploration, medicine, spaceflight, Mars, research, NASA)

Antonsen, Erik↗

NASA NTRSDate not supplied

An in-Time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.

IASMS↗