Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “shared and automated mobility”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Intelligent vehicle control: Opportunities for terrestrial-space system integration

For 11 years the Department of Defense has cooperated with a diverse array of other Federal agencies including the National Institute of Standards and Technology, the Jet Propulsion Laboratory, and the Department of Energy, to develop robotics technology for unmanned ground systems. These activities have addressed control system architectures supporting sharing of tasks between the system operator and various automated subsystems, man-machine interfaces to intelligent vehicles systems, video compression supporting vehicle driving in low data rate digital communication environments, multiple simultaneous vehicle control by a single operator, path planning and retrace, and automated obstacle detection and avoidance subsystem. Performance metrics and test facilities for robotic vehicles were developed permitting objective performance assessment of a variety of operator-automated vehicle control regimes. Progress in these areas will be described in the context of robotic vehicle testbeds specifically developed for automated vehicle research. These initiatives, particularly as regards the data compression, task sharing, and automated mobility topics, also have relevance in the space environment. The intersection of technology development interests between these two communities will be discussed in this paper.

Shoemaker, Charles↗
NASA NTRS2005

Expedition Memory: Towards Agent-based Web Services for Creating and Using Mars Exploration Data.

Explorers ranging over kilometers of rugged, sometimes "feature-less" terrain for over a year could be overwhelmed by tracking and sharing what they have done and learned. An automated system based on the existing Mobile Agents design [ I ] and Mars Exploration Rover experience [2], could serve as an "expedition memory" that would be indexed by voice as wel1 as a web interface, linking people, places, activities, records (voice notes, photographs, samples). and a descriptive scientific ontology. This database would be accessible during EVAs by astronauts, annotated by the remote science team, linked to EVA plans, and allow cross indexing between sites and expeditions. We consider the basic problem, our philosophical approach, technical methods, and uses of the expedition memory for facilitating long-term collaboration between Mars crews and Earth support teams. We emphasize that a "memory" does not mean a database per se, but an interactive service that combines different resources, and ultimately could be like a helpful librarian.

Clancey, William J.↗
NASA NTRS2008

Microwave Soil Moisture Retrieval Under Trees

Soil moisture is recognized as an important component of the water, energy, and carbon cycles at the interface between the Earth's surface and atmosphere. Current baseline soil moisture retrieval algorithms for microwave space missions have been developed and validated only over grasslands, agricultural crops, and generally light to moderate vegetation. Tree areas have commonly been excluded from operational soil moisture retrieval plans due to the large expected impact of trees on masking the microwave response to the underlying soil moisture. Our understanding of the microwave properties of trees of various sizes and their effect on soil moisture retrieval algorithms at L band is presently limited, although research efforts are ongoing in Europe, the United States, and elsewhere to remedy this situation. As part of this research, a coordinated sequence of field measurements involving the ComRAD (for Combined Radar/Radiometer) active/passive microwave truck instrument system has been undertaken. Jointly developed and operated by NASA Goddard Space Flight Center and George Washington University, ComRAD consists of dual-polarized 1.4 GHz total-power radiometers (LH, LV) and a quad-polarized 1.25 GHz L band radar sharing a single parabolic dish antenna with a novel broadband stacked patch dual-polarized feed, a quad-polarized 4.75 GHz C band radar, and a single channel 10 GHz XHH radar. The instruments are deployed on a mobile truck with an 19-m hydraulic boom and share common control software; real-time calibrated signals, and the capability for automated data collection for unattended operation. Most microwave soil moisture retrieval algorithms developed for use at L band frequencies are based on the tau-omega model, a simplified zero-order radiative transfer approach where scattering is largely ignored and vegetation canopies are generally treated as a bulk attenuating layer. In this approach, vegetation effects are parameterized by tau and omega, the microwave vegetation opacity and single scattering albedo. One goal of our current research is to determine whether the tau-omega model can work for tree canopies given the increased scatter from trees compared to grasses and crops, and. if so, what are effective values for tau and omega for trees.

O'Neill, P.↗
NASA NTRS2005

Automating CapCom Using Mobile Agents and Robotic Assistants

We have developed and tested an advanced EVA communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. This system, called Mobile Agents (MA), is voice controlled and provides information verbally to the astronauts through programs called personal agents. The system partly automates the role of CapCom in Apollo-including monitoring and managing EVA navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. EVA data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in the context of use, including six years of ethnographic observation of field geology. Our approach is to develop automation that supports the human work practices, allowing people to do what they do well, and to work in ways they are most familiar. Field experiments in Utah have enabled empirically discovering requirements and testing alternative technologies and protocols. This paper reports on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to move and wait in various locations to serve as a relay on the wireless network. The MA system is applicable to many space work situations that involve creating and navigating from maps (including configuring equipment for local topology), interacting with piloted and unpiloted rovers, adapting to environmental conditions, and remote team collaboration involving people and robots.

Clancey, William J.↗
NASA NTRSDate not supplied

Initial Development and Integration of a Vertiport Automation System for Advanced Air Mobility Operations

The High Density Vertiplex Sub-Project, as part of NASA’s Advanced Air Mobility (AAM) Project, has been developing a reference Vertiport Automation System (VAS) to support the management of arrival and departure operations in the terminal area of a vertiport or network of inter-connected vertiports known as a vertiplex. The VAS is potentially a key element of an integrated AAM architecture that will enable greater levels of coordination and predictability for vertiport users through its integration and sharing of information, and greater control of vertiport resources for managing operators. This paper provides an overview of the VAS and a description of an initial implementation that has been integrated into a broader reference architecture as part of ongoing research. Examples from recent simulations are presented with an outline for next steps and considerations.

vertiport↗
NASA NTRS2007

Automating CapCom Using Mobile Agents and Robotic Assistants

Mobile Agents (MA) is an advanced Extra-Vehicular Activity (EVA) communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. MA is voice controlled and provides information verbally to the astronauts through programs called "personal agents." The system partly automates the role of CapCom in Apollo-including monitoring and managing navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. Data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in authentic work contexts, including six years of ethnographic observation of field geology. Analog field experiments in Utah enabled empirically discovering requirements and testing alternative technologies and protocols. We report on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to serve as a relay on the wireless network.

Clancey, William J.↗
NASA NTRSDate not supplied

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management, FPM, AOP, UAM, deconflicti↗
NASA NTRSDate not supplied

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management↗
NASA NTRSDate not supplied

Uncrewed Lunar Surface Operations and Support Activities

Sustained human presence on the surface of the Moon and future missions to Mars require increased independence from surface crews and Earth-based mission control to operate efficiently, safely, and reliably. The time for surface crews to perform tasks will be limited. Extravehicular activities by surface personnel are burdensome and time-consuming, even when a continuous human presence on the surface occurs. Identifying and balancing human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle will be essential to achieve mission objectives. Among these objectives are attaining a sustained human presence, improving performance and mission effectiveness, reducing operations and maintenance (O&M) costs, and ensuring operations that are robust to communication delays. To achieve these objectives, an operational shift toward increased automation and autonomy with less reliance on humans is needed. Uncrewed lunar surface operations and support activities occur when surface crews are not present or are independent of surface crew timeline activities requiring no surface crew oversight or intervention. These uncrewed surface opportunities can also be planned to minimize crew workload that avoids routine maintenance and support tasks, thus maximizing crew exploration time. Uncrewed preparations such as staging and prepositioning equipment and materials before the crew arrives could improve crew task efficiency. Additional opportunities exist to conduct uncrewed science, exploration, and utilization. Uncrewed surface architecture functions can include science and exploration; habitation; launch and landing support; surface communication and navigation; surface power generation and distribution; human surface mobility; lifting, handling, manipulating; excavation, construction, and site preparation; logistics management; maintenance and repair; surface resource utilization; integrated site operations and shared support services (e.g., site scheduling/prioritization, dust mitigation/contamination control, and surface safety). Early robotic lunar surface campaigns will provide information on the availability of resources, such as oxygen and water, and demonstrate surface-based technologies. After the Artemis III human lunar return mission, a series of landers will deliver surface systems, cargo, supplies, science packages, spare parts, and commodities. A balance of crewed and uncrewed surface operations will enable a sustained lunar surface presence at the South Pole of the Moon at a site that will be known as the Artemis Base Camp (ABC). It is envisioned that base camp operations on and around the Moon will then help prepare for the mission durations and activities needed to support the first human mission to Mars. Before long-duration crew missions to the base camp can occur, the necessary surface infrastructure will be pre-deployed and verified operational. Surface assets will be teleoperated and remotely managed from Earth. Additionally, robotic and short-duration crewed missions to the ABC will ensure the site’s merit to achieve long-term science objectives, availability of usable resources, and that terrain, seasonal variations, and illumination conditions are acceptable. ABC will consist of different areas where specific functions and services are rendered, including: • Launch and Landing Area • Habitation Area • Power Production Area • Resource Areas Launch and Landing Area—The launch and landing area will support associated functions for the arrival and departure of vehicles, such as crewed landing and ascent and uncrewed cargo deliveries and offloading. It will evolve from an unimproved site at the beginning of the exploration campaign to a more sustainable landing and launch area that can support repeated arrivals and departures. Initial uncrewed Lunar Terrain Vehicle (LTV) surface operations may include emplacement of navigation beacons and communication equipment, real-time video and photography of landing/liftoff events, and element repositioning, such as portable utility power (PUP) (applicable for other landed assets at other areas). Site preparations, such as surface leveling, soil compaction, and berm/path construction, may be needed for a more sustainable launch and landing area capable of accommodating vehicles that are increasingly more reusable and reduce the effects of plume surface interactions and ejecta impacts on nearby surface assets. During the ABC missions, cargo and logistics will be delivered to the lunar surface via robotic cargo landers before the crew arrives. These shipments, which can arrive in pressurized logistics carriers, will deliver the logistics necessary to support a crewed mission and include items such as food, water, equipment spares, etc. Providing the capability to retrieve, offload, and transport the logistics closer to the ABC site before the arrival of the crew will increase the overall efficiency of crew operations once they arrive. In the sustained phase of exploration, other supporting services may be needed, such as lander propellant servicing, surface power services, commodity refreshes, and additional inspection, maintenance, and repair capabilities, to sustain a cadence of extended personnel stays and cargo arrivals and departures. Habitation Area—Uncrewed support to surface habitation could involve supporting activation and pre-entry operations of the habitat while the crew is in orbit at the Gateway outpost preparing for a surface landing. Surface Habitat (SH) uncrewed operations may include bringing the cabin environment to a habitable temperature and air mix and activating other critical crew support systems. Potential crop production uncrewed tasks in the SH could also include autonomous watering and tending. Additionally, when the crew departs, the SH enters dormancy for the long period of uncrewed operation. A logistical staging area could also be collocated near the SH. If so, staging operations for crew supplies, waste re-location, and recycling operations may be opportunities for uncrewed operations. Power Production Area—The Fission Surface Power (FSP) element and its supporting distribution equipment provide power to surface elements as needed across the ABC to supplement day-to-day operations and survive lunar nights. Uncrewed support of this power system includes any initial LTV-assisted deployments of cables and other distributed equipment, associated electrical connections, and system testing and activation operations. Robotically performing some inspections, maintenance, or repair tasks on the power distribution equipment could reduce the surface crew workload. Resource Area— Uncrewed resource prospecting, mapping, and characterizing possible resource sites is likely to be time-consuming and represents an opportunity for uncrewed operations between crewed missions. Uncrewed mobile equipment operations will be needed in the extreme environments of permanently shadowed locations where resource extractions occur. As In-Situ Resource Utilization (ISRU) pilot plant operations begin, uncrewed surface support activities with available mobile and portable assets (LTV, PUP, etc.) will better support these operations. Any produced commodities can be stored at a centralized storage location for future use. Also associated with these operations is the use of mobile robotic excavators for resource acquisition and robotic/autonomous regolith processing. The waste tailings generated during excavation and regolith processing would also need to be transported and deposited at a dedicated location. Surface assets will continue operating between crew visits to maintain surface capabilities, conduct lunar surface science, technology demonstrations, and public outreach opportunities. Additionally, certain sustaining tasks that would consume valuable crew time could be performed before crew arrival, or after their departure. This capability may offer more affordable options to construct, activate, test, and maintain a broad set of surface assets. Telerobotically operated human surface mobility systems, such as the LTV and Pressurized Rover (PR), can be utilized for various tasks. Surface environmental conditions pose a distinct challenge for all these activities. Surface illumination and localized shadows are one such factor. Night-survival operations could consist of thermal management, battery pre-charging, and load shedding. Some surface systems may hibernate through the night and then awake and continue nominal operations. Uncrewed mobile assets may use a more adaptive approach to optimize their power and operations; one method is to follow the sunlight. Night-survival operations may be initiated remotely by teleoperation, automated, or accomplished by supervised autonomous operation. The ability to pre-deploy and control remote assets in orbit or on Mars before the arrival of the mission crew is a key capability that can be simulated on the moon. The base camp provides a venue where these advanced operational concepts, technologies, and autonomous methods and techniques, including the incorporation of time delays to simulate Earth-Mars latency can be replicated to help buy down future Mars mission risks. This paper will examine the evolution of uncrewed lunar surface operations and support activities. It will also discuss the lunar surface environmental conditions (thermal, lighting, terrain, topography, communications) along with the challenges they pose on uncrewed surface operations, and the performance of these activities with limited to minimal human interaction and/or teleoperation. Since lunar missions include Mars mission analogs, such investigation provides the framework for future uncrewed Mars mission support.

Mark E Lewis↗
NASA NTRS2025

Provider of Services for Urban Air Mobility (PSU) Prototype Simulation (X5) Final Report

Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and air traffic automation technologies. NASA has conducted a series of simulations, called the X-series simulation, to evaluate the UAM concept of operations and support the development of airspace procedures and services for UAM operations. The simulation called “X5” was conducted in 2023 to test a Provider of Services for UAM (PSU) prototype developed by NASA for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In this simulation, two strategic conflict management capabilities, Demand-Capacity Balancing and Sequencing and Scheduling, were further investigated. This document describes the UAM system architecture modeled, the X5 simulation environment to be executed (e.g., traffic scenario and UAM airspace construct), and the strategic conflict management processes developed and evaluated in this study. Then, the simulation results are provided using several system performance metrics, such as the number of operations planned and activated, demand-capacity imbalances detected and resolved, and pre-departure delays. Based on these metrics, the test findings and lessons learned from this simulation are discussed. NASA developed a PSU prototype as part of a reference implementation of UAM system architecture and evolved strategic conflict management capabilities for UAM operations from the previous collaborative simulations with industry partners. Below is the summary of the achievements: - Aligned NASA’s UAM reference architecture with the FAA’s UAM ConOps notional architecture - Extended UAM airspace management capabilities to include 1) Demand-Capacity Balancing (DCB) to ensure operators coordinate planned usage of shared vertiports, and 2) Sequencing and Scheduling (S&S) at UAM corridor entry and exit points to help facilitate an orderly flow of traffic - Defined the PSU information exchange APIs and requirements towards informing industry standards - Developed and tested a NASA PSU prototype as reference implementation to validate the requirements and APIs - Developed a prototype service connecting NASA’s PSU and the FAA system for testing future PSU-ATM interface requirements - Tested NASA-developed assumptions for UAM operations such as airspace design, procedures, vehicle performance, and strategic conflict management methods to inform future Cooperative Operating Practices (COPs) development with industry - Evaluated system performance metrics such as number of simultaneous operations and ground delays that can help define system-level requirements. The simulation results showed that the UAM traffic demand could be managed to minimize the needs of tactical separation provision with ground delays assigned by DCB and S&S. These accomplishments and the lessons learned from the PSU Prototype X5 simulation activities will be valuable inputs for the Air Mobility Pathfinders (AMP) project, which is NASA’s new project to create and evaluate a reference architecture for safe, secure, and scalable UAM operations.

Simulation↗
NASA NTRS2024

Federal USS Synthesis Effort: 2023 Flight Test Report. A NASA and Department of Defense Joint Evaluation of Multi-Domain Airspace Integration

In recent years, advancements in technology have greatly improved the utility and applicability of Uncrewed Aircraft Systems (UAS) and have highlighted the need for and importance of UAS Traffic Management (UTM). Onboard sense and avoid systems, ground-based sensors, and long- range command and control (C2) systems have significantly expanded the possibilities for UAS beyond visual line of sight (BVLOS) operations. Initially, research on UTM flights focused on their interactions with other UTM operations, but that has since been expanded to include interactions with the flight profiles of Advanced Air Mobility (AAM) and upper Class E Traffic Management (ETM) operations. Recognizing the potential of these systems and the increase in UAS autonomy, the Department of Defense (DoD) is working towards integrating these missions and systems into a unified DoD Federal ecosystem. The Federal USS Synthesis Effort (FUSE) aims to develop a live system that can efficiently combine this wide range of UTM, AAM, and ETM systems, thus enabling expanded operations within a single common operating environment. The goal of the Federal USS Synthesis Effort (FUSE) is for NASA and the DoD to develop a live system that can efficiently combine UTM, AAM, and ETM systems. The most recent endeavor in this effort was a live flight test conducted near Grand Forks Air Force Base in June, 2023, where the FUSE ecosystem successfully demonstrated integrating UTM, AAM, and ETM operations while providing a single, shared COP to users. Additional investigations were made during the test, including assessing the usefulness of the system and its capability to support UAS weighing over 55 lbs.; testing user messaging capabilities and a DoD adaptation of a Federal USS; and assessing user workload, automated vs manual control, and the usability of NASA’s XTMClient.

Federal USS↗
NASA NTRSDate not supplied

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

Urban Air Mobility (UAM) is a new transportation concept that enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. To achieve the high level of operational density and complexity desired by the UAM community, an airspace system that allows UAM operators to readily access and operate safely and efficiently in the airspace is needed. This airspace system will require air traffic management designed to reduce the risk of conflicts and loss of separation between UAM flights. In general, strategic conflict management is considered as the first layer of conflict management for safe flight operations to condition the traffic to reduce the need for airborne separation provision, the second layer of conflict management. Demand Capacity Balancing (DCB) is one of the concept components to achieve strategic conflict management. DCB strategically evaluates traffic demand and resource capacities to allow UAM operators to determine when, where and how they operate, while mitigating conflicting needs for airspace and vertiport capacity. DCB can be applied whenever UAM demand exceeds the capacity in airspace or at vertiports. As the UAM ecosystem evolves with advanced technologies and matured operational procedures, more complicated conflict management will likely be needed. In the current UAM ‘Concept of Operation (ConOps) 1.0’ operational stage defined by FAA, however, it will be meaningful to explore the demand capacity balancing at vertiports only, as an initial strategic conflict management approach for UAM operations because vertiport capacity seems to be a bottleneck of UAM traffic. For this research, we developed a demand-capacity imbalance detection and resolution service for UAM. This DCB service identifies the demand from operators and compares the demand to a given capacity at the shared resources (i.e., vertiports) over the upcoming time horizon which is divided into time bins having a constant interval. When a new flight plan is submitted, the algorithm embedded in the DCB service checks the available time bins based on the desired departure time and estimated arrival time at origin and destination vertiports, respectively. If the time bins for the originally desired times are already occupied by other flights (i.e., demand is at or above capacity), the algorithm finds the next available time bins for takeoff and landing and shifts the conflicting departure time to the earliest time that satisfies the capacity constraints at both origin and destination vertiports. The details of the algorithm will be described in the final manuscript. Figure 1 shows that the proposed DCB algorithm works well for a sample traffic scenario. In this example, a total of 144 flights, split between two operators, are planned over 2 hours, traveling 10 routes between five vertiports. In the heatmaps, the horizontal axis shows 12 time bins where each bin represents a 12-minute interval, and the vertical axis shows five vertiports. The number in each cell shows the number of operations, counting both departures and arrivals, at a specific vertiport in each time bin. For the given capacity of 2 operations/vertiport/bin, Figure 1 shows that the original demand sometimes exceeds the capacity, but the modified demand is reduced to the given capacity after resolving demand-capacity imbalances. When UAM flights are operated, it is expected that many practical issues would arise in the federated system architecture with multiple operators. UAM operators may experience a time synchronization issue due to communication delay between operator and vehicle. UAM vehicles would fly at different flight speeds, depending on vehicle models. Actual departure and arrival times can have large variations, compared to the schedule. The lead time from flight plan submission to desired departure time can vary by service type (e.g., regular shuttle service vs. on-demand service). Using the proposed DCB algorithm, we also investigated how the actual flight schedule and DCB performance are affected by these uncertainties such as unsynchronized times between operators, flight speed differences, lead time differences, and departure time errors. The final manuscript will include the background of this research work, the description of the DCB algorithm and its use cases with traffic scenarios. It will also provide the analytical results about the impact of various uncertainties that can occur in actual UAM operations on the DCB at vertiports, in terms of demand distribution changes, number of simultaneous operations, and delay propagation.

Urban Air Mobility↗
NASA NTRS2020

UAM Vision Concept of Operations (ConOps) UAM Maturity Level (UML) 4

This 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. This concept has generated tremendous interest and industry investment. UAM envisages a future in which advanced technologies and new operational procedures enable practical, cost-effective air travel as an integral mode of transportation in metropolitan areas. It represents one of the most exciting and complex AAM concepts with highly automated aircraft providing commercial services to the public over densely populated cities. For this reason, the National Aeronautics and Space Administration (NASA) selected UAM as the initial goal of its AAM efforts and the focus of this Vision Concept of Operations (ConOps) document. UAM Community Vision ConOps: This Vision ConOps effort was led by experts from NASA’s Aeronautics Research Mission Directorate (ARMD) in collaboration with the Federal Aviation Administration (FAA) and Deloitte’s Ecosystem Advisory Group (a cohort of advisers with aviation, aerospace, and regulatory expertise). To develop this Vision ConOps, NASA, FAA, and Deloitte built upon the current body of aeronautical research and consulted with more than 100 stakeholder organizations. This UAM community includes entities ranging from legacy aviation leaders to innovators and new market entrants. Stakeholders consulted included the federal government, state and local government, aerospace original equipment manufacturers (OEMs), local transportation organizations, prospective UAM operators, academia, industry standards-setting bodies, airports, service suppliers, and others (as described in Appendix G). This input was captured through the following methods: • A series of more than two dozen interviews with industry experts, federal regulators, state and local governments, and industry trade groups provided insight into the challenges of UAM integration into the National Airspace System (NAS), as well as technology developments and a variety of perspectives as to how UAM systems will integrate. • A series of two-day community workshops enabling active, detailed engagement of nearly 100 industry, academic, federal, and state stakeholder individuals. These workshops, hosted by NASA and Deloitte, explored UAM concepts in detail, and stakeholders were invited to collaboratively analyze and propose solutions to some of the greatest conceptual challenges behind UAM at an intermediate state. • A review of more than 160 sources of UAM literature from across government, industry, and academia, which are listed in Appendix H. • The public sharing of workshop input and document drafts for review and input across the UAM community. Feedback in the form of more than 1,000 comments and inputs on the document was received from industry groups, individual companies, academia, and government (federal, state, and local), among others. Although effort was made to incorporate inputs from across the UAM stakeholder group, not all comments could ultimately be incorporated in this version. The team resolved conflicting comments or ideas while maintaining consistency with the known direction of regulators and ensuring the document was coherent and consistent. It is recognized that this is a rapidly evolving area and that concepts will likely change over time; as such, this Vision ConOps is a living document and is expected to evolve as concepts mature. The ConOps does, however, provide a vision of UAM concepts and solutions based on the broad insights from across the UAM stakeholder community at the time of its publication and is intended to serve as a UAM North Star for continued research and development of UAM. As a broad Vision ConOps, is not a detailed engineering document; rather, it focuses primarily on outlining a broad, high-level vision across all aspects of a UAM transportation system.

Urban Air Mobility↗
NASA NTRSDate not supplied

Delay Tolerant, Radio Frequency Identification (RFID )-enabled Sensing

Radio Frequency Identification (RFID) technology offers a completely passive method to transmit fixed data sequences from an RFID tag, which typically doesn’t have its own power supply, to an interrogator. Radio frequency (RF) energy harvested from the interrogator is rectified by the tag and used to charge an integrated circuit (IC). The IC then modulates the received signal with the data stored on the tag and reflects the energy back to the interrogator. RFID has seen great proliferation in terrestrial inventory management applications, and it has recently made the jump to spaceflight applications onboard the International Space Station, augmenting an existing optical bar‐code infrastructure for tracking supplies. A number of advanced automated logistics management (ALM) concepts employing RFID are currently being developed and evaluated, including so‐called “smart” shelves, cubbies, and trash receptacles using low‐power, embeddable RFID interrogators. An infrastructure where both crew members and robotic assistants, such as autonomous free flyers, are similarly equipped with small RFID interrogators seems likely. It therefore behooves us to consider extending this infrastructure beyond ALM to applications such as low power, embedded sensing. Typically, data on an RFID tag can only be written by an RFID interrogator, using interrogator energy. In recent years, however, a few efforts have focused on using that energy to drive data acquisition from the tag IC, allowing the tag to modify its stored data sequence with sensor data before replying to an interrogator. In this way, the tag can act as a completely passive sensing device. One problem exists with this approach, however: the tag cannot gather data when an interrogator is not present. Thus, strictly passive RFID sensing tags cannot gather data at regular intervals, in the manner of a typical wireless sensor network, without careful, and impractical, planning of mobile interrogator movements. To address this shortcoming, we look to a recent advance in RFID technology which allows an external microprocessor to power the tag IC and write directly into its RFID memory using a wired serial interface. In this paradigm, data gathering is driven by a small, on‐board power supply (using batteries or harvested energy), and data transfer is provided passively through the RFID interrogation service. Since communication typically consumes the lion’s share of power in WSNs, such a technique has the potential to enable extremely long‐lived, embedded wireless sensing when used with extremely low‐current microcontrollers. Since the communication channel is only open when an interrogator is present and actively interrogating the RFID sensing tag, transport of periodically‐sampled sensor data presents itself as a delay/disruption‐tolerant networking (DTN) problem. In this paper, we present the design of a DTN‐like overlay on the common EPC Global, Class 1, Generation 2 RFID standard. This overlay allows seamless, guaranteed data transfer using the EPC Global protocol, supporting extremely low‐power, embedded sensing using an infrastructure likely to be already in place for ALM applications. We evaluate a prototype implementation of a complete end‐to‐end system using a robotic RFID interrogation agent, and we present future directions for the development of this sensing technique.

Raymond S. Wagner↗
NASA NTRSDate not supplied

Streamlining Tactical Operator Handoffs During Multi-Vehicle Operations

Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies over time. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool made subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.

m:N operations↗
NASA NTRS2019

Airspace Technology Demonstration 2 (ATD-2) Phase 2 Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline and Phase 2 Fused demonstrations of the Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration’s (NASA) Airspace Technology Demonstration 2 (ATD-2) project, which has been demonstrated since October of 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA has been developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport operators, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation’s most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research has been demonstrated at the CLT airport since the beginning of October 2017. Phase 1 provided data exchange and integration with the initial demonstration of the integrated system of strategic and tactical scheduling, collaborative tactical surface metering, tactical departure scheduling to an en route meter point and overhead stream insertion, initial integration of a TFDM SWIM prototype feed, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 The Phase 2 Fused IADS system provided substantial updates to baseline IADS Demonstration capability. Improvements were made to the IADS modeler; tactical surface scheduling, and metering; tactical departure scheduling for overhead stream insertion; Electronic Flight Data (EFD) and the integration with the FAA Advanced Electronic Flight Strip (AEFS); RTC/RMTC, and departure trajectories. New capabilities included a TFDM SWIM prototype feed and delivery of IADS data via the TFDM Terminal Publication (TTP) service of the FAA’s SWIM system; strategic surface scheduling and metering as well as fusion with tactical surface metering; integration and ingestion of data from TTP-connected Mobile App and texting industry for General Aviation (GA) flights; and expansion of airspace deployments to include adjacent Center automation, in particular interface with the Atlanta Center (ZTL) arrival metering TBFM system to evaluate pre-scheduling of flights. Improvements in Data Analysis and System Health (DASH) monitoring and updates were completed as well.

Talebi, Ehsan↗
NASA NTRSDate not supplied

Streamlining Tactical Operator Handoffs During Multi-Vehicle Applications

Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies overtime. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool make subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.

M:N operations↗
NASA NTRSDate not supplied

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗