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DOE OSTI2022

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1991

The ELLIPSO (tm) system: Elliptical low orbits for mobile communications and other optimum system elements

On 5 Nov. 1990, Ellipsat filed with the FCC the first application to provide voice communication services via low earth orbiting (LEO) satellites. The proposed system, ELLIPSO, aims at achieving end-user costs comparable to those in the cellular industry. On 3 Jun. 1991 Ellipsat filed for the second complement of its system. Ellipsat was also the first company to propose combined position determination and mobile voice services via low-earth orbiting satellites. Ellipsat is still the only proponent of elliptical orbits for any commercial system in the United States. ELLIPSO uses a spectrum efficient combination of FDMA and CDMA techniques. Ellipsat's strategy is to tailor required capacity to user demand, reduce initial system costs and investment risks, and allow the provision of services at affordable end-user prices. ELLIPSO offers optimum features in all the components of its system, elliptical orbits, small satellites, integrated protocol and signalling system, integrated end-user electronics, novel marketing approach based on the cooperation with the tenets of mobile communications, end-user costs that are affordable, and a low risk approach as deployment is tailored to the growth of its customer base. The efficient design of the ELLIPSO constellation and system allows estimated end-user costs in the $.50 per minute range, five to six times less than any other system of comparable capability.

Castiel, David↗

NASA NTRS2000

The Future of the Internet in Science

How are scientists going to make use of the Internet several years from now? This is a case study of a leading-edge experiment in building a 'virtual institute'-- using electronic communication tools to foster collaboration among geographically dispersed scientists. Our experience suggests: Scientists will want to use web-based document management systems. There will be a demand for Internet-enabled meeting support tools. While internet videoconferencing will have limited value for scientists, webcams will be in great demand as a tool for transmitting pictures of objects and settings, rather than "talking heads." and a significant share of scientists who do fieldwork will embrace mobile voice, data and video communication tools. The setting for these findings is a research consortium called the NASA Astrobiology Institute.

Guice, Jon↗

NASA NTRS2022

Scheduling For Urban Air Mobility Using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗

NASA NTRSDate not supplied

Scheduling for Urban Air Mobility using Safe Learning

Urban Air Mobility↗

DOE OSTI2026

BEAM CORE: A Flexible Ecosystem for Freight, Demographics, and Vehicle Analysis

The Behavior, Energy, Autonomy, and Mobility Comprehensive Regional Evaluator (BEAM CORE) is an open-source, modular ecosystem of highly refined, agent-based modeling tools developed by Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies. Organizations such as metropolitan planning organizations, agencies, and companies can use BEAM CORE to analyze freight movement and optimize logistics solutions, assess the impacts of emerging freight technologies or e-commerce trends, model dynamic population growth and evolution, and understand the drivers and impacts of electric vehicle adoption across households in a given region. Users can choose from a flexible suite of modeling modules according to their needs and priorities. The modules integrate with travel demand models to support enhanced analysis of diverse scenarios involving freight movement, vehicle technologies, and other key factors relevant to regional planning.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Low Ohmic contact resistance and high on/off ratio in transition metal dichalcogenides field-effect transistors via residue-free transfer

Beyond-silicon technology demands ultrahigh performance field-effect transistors. Transition metal dichalcogenides provide an ideal material platform, but the device performances such as the contact resistance, on/off ratio and mobility are often limited by the presence of interfacial residues caused by transfer procedures. Here, we show an ideal residue-free transfer approach using polypropylene carbonate with a negligible residue coverage of ~0.08% for monolayer MoS 2 at the centimetre scale. By incorporating a bismuth semimetal contact with an atomically clean monolayer MoS 2 field-effect transistor on hexagonal boron nitride substrate, we obtain an ultralow Ohmic contact resistance of ~78 Ω µm, approaching the quantum limit, and a record-high on/off ratio of ~10 11 at 15 K. Further, such an ultra-clean fabrication approach could be the ideal platform for high-performance electrical devices using large-area semiconducting transition metal dichalcogenides.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRS2016

Optical Breath Gas Extravehicular Activity Sensor for the Advanced Portable Life Support System

The function of the infrared gas transducer used during extravehicular activity (EVA) in the current space suit is to measure and report the concentration of carbon dioxide (CO2) in the ventilation loop. The next generation portable life support system (PLSS) requires highly accurate CO2 sensing technology with performance beyond that presently in use on the International Space Station extravehicular mobility unit (EMU). Further, that accuracy needs to be provided over the full operating pressure range of the suit (3 to 25 psia). Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. A laser diode (LD) sensor based on infrared absorption spectroscopy is being developed for this purpose by Vista Photonics, Inc. Version 1.0 prototype devices were delivered to NASA Johnson Space Center (JSC) in September 2011. The prototypes were upgraded with more sophisticated communications and faster response times to version 2.0 and delivered to JSC in July 2012. The sensors incorporate a laser diode based CO2 channel that also includes an incidental water vapor (humidity) measurement. The prototypes are controlled digitally with an field-programmable gate array microcontroller architecture. Based on the results of the iterative instrument development, further prototype development and testing of instruments were performed leveraging the lessons learned where feasible. The present development extends and upgrades the earlier hardware for the advanced PLSS 2.5 prototypes for testing at JSC. The prototypes provide significantly enhanced accuracy for water vapor measurement and eliminate wavelength drift affecting the earlier versions. Various improvements to the electronics and gas sampling are currently being advanced including the companion development of engineering development units that will ultimately be capable of radiation tolerance. The combination of low power electronics with the performance of a long wavelength laser spectrometer enables multi-gas sensors with significantly increased performance over that presently offered in the EMU.

Wood, William R.↗

DOE OSTI2022

Clean Energy Transition for Transportation Systems: Modeling Implications

Transportation is currently the least-diversified energy demand sector, with over 90% of energy use coming from petroleum. As a result, transportation recently became the largest source of GHG emissions in the U.S. and mobility needs for passenger and freight are growing rapidly. However, after over a century of petroleum dominance, new disruptive technologies and business models offer a pathway to decarbonize the sector. Transportation is at a turning point. On the horizon lies a future where affordable and abundant renewable electricity can be used to power cost-competitive battery electric vehicles (EVs) and produce energy-dense low-carbon fuels enabling to fully decarbonize transportation systems across all modes. Exploring the clean energy transition for the multitude of different transportation systems requires new analytical modeling and approaches. This talk reviewed current work at the National Renewable Energy Laboratory (NREL) to develop and use innovative tools and analytics approaches to inform the transformation to a sustainable mobility future and the integration of transportation systems with the broader energy sector.

ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2023

U.S. Spacesuit Knowledge Capture – Expanding Our Future

NASA is going to the Moon. And it will don a new spacesuit when it reaches its destination. NASA is partnering with industry to build the spacesuit and supporting systems (i.e., surface mobility tools) that astronauts will use on the Moon, starting with Artemis III. The Johnson Space Center’s (JSC) Extravehicular Activity and Human Surface Mobility Program (EHP) is managing this effort, and the U.S. Spacesuit Knowledge Capture (SKC) Program is expanding its scope to help. For 15 years, the SKC Program has collected, archived, and disseminated decades of spacesuit-related knowledge, as appropriate, to help NASA scientists, technicians, and engineers support space exploration. The SKC Program captures its knowledge by hosting and recording subject-matter expert (SME) lectures, interviews, and workshops. It also collects retired SMEs’ reports, drawings, and schematics containing legacy spacesuit knowledge. To build a technically capable spacesuit essential for future lunar exploration, spacesuit professionals borrowed much of their knowledge from legacy Extravehicular Activity (EVA) spacesuits. Most of the SKC Program’s captured knowledge has focused on legacy and current spacesuits. To support EHP, the SKC Program is expanding its knowledge capture focus beyond the spacesuit and will seek to collect knowledge from other pertinent topics (e.g., Lunar Terrain Vehicle and EVA tools). In 2007, the SKC Program began as an independent source, without funding. As demand for capturing essential spacesuit knowledge increased, consequently, the SKC Program’s funding increased. Expansion of the SKC Program was evident in 2019, when it seized the opportunity to capture the Exploration Extravehicular Mobility Unit (xEMU) buildup at JSC. In 2021, its collaboration with the xEMU Technical Community of Practice facilitated training and knowledge sharing with the xEMU team. In 2022, the SKC Program began supporting EHP. This paper describes the SKC Program’s expansive evolution, plans to support EHP, and more.

Cinda Chullen↗

NASA NTRS2020

Electrical Cable Design for Urban Air Mobility Aircraft

Urban Air Mobility (UAM) describes a new type of aviation focused on efficient flight within urban areas for moving people and goods. There are many different configurations of UAM vehicles, but they generally use an electric motor driving a propeller or ducted fan powered by batteries or a hybrid electric power generation system. Transmission cables are used to move energy from the storage or generation system to the electric motors. Though terrestrial power transmission cables are well established technology, aviation applications bring a whole host of new design challenges that are not typical considerations in terrestrial applications. Aircraft power transmission cable designs must compromise between resistance-per-length, weight-per-length, volume constraints, and other essential qualities. In this paper we use a multidisciplinary design optimization to explore the sensitivity of these qualities to a representative tiltwing turboelectric UAM aircraft concept. This is performed by coupling propulsion and thermal models for a given mission criteria. Results presented indicate that decreasing cable weight at the expense of increasing cable volume or cooling demand is effective at minimizing maximum takeoff weight (MTO). These findings indicate that subsystem designers should update their modeling approach in order to contribute to system-level optimality for highly-coupled novel aircraft. Mobility (UAM) vehicles have the potential to change urban and intra-urban transport in new and interesting ways. In a series of two papers Johnson et al.1 and Silva et al.2 presented four reference vehicle configurations that could service different niches in the UAM aviation category. Of those, this paper focuses on the Vertical Take-off and Landing (VTOL) tiltwing configuration shown in Figure 1. This configuration uses a turboelectric power system, feeding power from a turbo-generator through a system of transmission cables to four motors spinning large propellers on the wings. Previous work on electric cable subsystems leaves much yet to be explored, especially in the realm of subsystem coupling. Several aircraft optimization studies1, 3, 4 only considered aircraft electrical cable weight and ignored thermal effects. Electric and hybrid-electric aircraft studies by Mueller et al.5 and Hoelzen et al.6 selected a cable material but did not investigate alternative materials. Advanced cable materials have been examined by a number of authors: Alvarenga7 examined carbon nanotube (CNT) conductors for low-power applications. De Groh8, 9 examined CNT conductors for motor winding applications. Behabtu et al.,10 and Zhao et al.11 examined CNT conductors for a general applications. There were some studies that examined the thermal effects of cables but they did not allow the cable material to change; El-Kady12 optimized ground-cable insulation and cooling subject constraints. Vratny13 selected cable material based on vehicle power demand, and required resulting cable heat to be dissipated by the Thermal Management System (TMS). None of these previous studies allowed for the selection of the cable material based on a system level optimization goal. Instead, they focused on sub-system optimality such as minimum weight, which comes at the expense of incurring additional costs for other subsystems. Dama14 selected overhead transmission line materials using a weighting function and thermal constraints. However, that work was not coupled with any aircraft subsystems like a TMS. The traditional aircraft design approach, which relies on assembling groups of optimal subsystems, breaks down when considering novel aircraft concepts like the tiltwing vehicle. In a large part, this is because novel concepts have a much higher degree of interaction or coupling between subsystems. For example, when a cable creates heat, this heat needs to be dissipated by the TMS, which needs power supplied by the turbine, and delivering the power creates more heat. The cable, the TMS, and the turbine are all coupled. A change to one subsystem will affect all the other subsystems, much to the consternation of subsystem design experts. Multidisciplinary optimization is the design approach that can address these challenges. However, to fully take advantage of this, we must change the way we think about subsystem design. Specifically, we must move away from point design, and focus on creating solution spaces. The work presented in this paper uses the multidisciplinary optimization approach with aircraft level models to study the system-level sensitivity of cable traits: weight-per-length and resistance-per-length. Additionally, we examined the effects of vehicle imposed volume constraints on these traits. This is useful for three purposes: (1) to demonstrate a framework that can perform a coupled analysis between the aircraft thermal and propulsion systems, (2) to provide a method by which future cable designs can be evaluated against each other given a system-level design goal, (3) to provide insight into what cable properties may be promising for future research. This last element is explored given the caveat that the models contained in this analysis do not represent high-fidelity systems. Thus, while we can demonstrate coupling in between systems, the exact system-level sensitivity to a given parameter may change if a subsystem model or the assumptions governing that model change. The organization of this paper is as follows, in Sec II we outline a method to combine the VTOL vehicle design and cable information in order to produce cables sensitivity studies. Results analysis and discussion are contained in Sec III. Conclusions are presented in Sec IV.

Aretskin-Hariton, Eliot D.↗

DOE OSTI2020

Real-time Ridesharing for Transportation Hubs with Demand and Supply Uncertainty

Transportation hubs in major cities generate a significant amount of trips by taxis and for-hail vehicles (FHV), with many of the trips sharing similar destinations. This suggests promising opportunities to leverage the collective travel needs with dedicated ridesharing solutions to reduce the externalities of excessive traffic at transportation hubs. In this study, we develop a novel dynamic ridesharing approach to serve trips from the transportation hub by considering (1) demand (new passengers) and supply (newly available vehicles) in the near future and (2) the uncertainty of future predictions. Our approach consists of two stages. In the first stage, we develop a data structure called hub mobility tree to generate potential combinations of shareable trips as candidate schedules efficiently. Then the generated schedules are used in the second stage to formulate the stochastic hub-based ridesharing problem (SHRP), which is a stochastic integer programming problem with the objective to maximize the total expected ridesharing profit over time. Due to the prohibitive number of shareable trips, we then approximately solve SHRP by the sample average approximate method (SAA), and a dual Lagrangian technique is implemented to further improve the scalability of the solution approach. We demonstrate the performances of the proposed method by simulating the ridesharing service at JFK airport using NYC taxi and FHV data. The results indicate that the proposed method outperforms the myopic ridesharing (maximize profit for a single time step) and the rolling horizon method with point estimation of future demand and supply.

dynamic ridesharing↗

DOE OSTI2024

SmartTransit.AI: A Dynamic Paratransit and Microtransit Application

New rideshare and shared mobility services have transformed urban mobility in recent years. Such services have the potential to improve efficiency and reduce costs by allowing users to share rides in high-capacity vehicles and vans. Most transit agencies already operate various ridepooling services, including microtransit and paratransit. However, the objectives and constraints for implementing these services vary greatly between agencies and can be challenging. First, off-the-shelf ridepooling formulations must be adapted for real-world conditions and constraints. Second, the lack of modular and reusable software makes it hard to implement and evaluate new ridepooling algorithms and approaches in real-world settings. We demonstrate a modular on-demand public transportation scheduling software for microtransit and paratransit services. The software is aimed at transit agencies looking to incorporate state-of-the-art rideshare and ridepooling algorithms in their everyday operations. We provide management software for dispatchers and mobile applications for drivers and users and conclude with results from the demonstration in Chattanooga, TN.

Pavia, Sophie↗

DOE OSTI2025

Energy-efficient multimodal mobility networks in transportation digital twins: Strategies and optimization

The study proposes a comprehensive Transportation Mobility (TransitMo) framework covering conceptual design, model formulation, optimization, simulation, and impact analysis of the transportation mobility system. TransitMo is composed of a transportation digital twin developed in Simulation of Urban MObility (SUMO) and an Intelligent Traffic Management and Control Center (ITMCC) that identifies the best ways to improve the movement of people within urban areas using various modes of transportation. This study encompasses advanced modeling techniques, algorithms, and strategic testing to optimize energy efficiency and mobility in a multimodal shared mobility network. TransitMo’s practical applications are exemplified through a city-scaled simulation network in Chattanooga, TN, employing demographic data to analyze historical traffic patterns and forecast future demands. Central to this methodology are three models: the User Preference Model (UP), the Energy Consumption Model (EC), and the System Optimization Model (SO). These models work in concert to iteratively devise the optimal travel incentives and minimize the total system cost in a real-time manner. In conclusion, test results verified that the proposed adaptive incentive program and optimized bus scheduling can improve network performance by increasing public transit ridership.

42 ENGINEERING↗

NASA NTRS1978

Coal's role in California's energy needs

California's post-industrial society demands confidence in the energy supply system as an essential ingredient for social harmony and adequate job creating capital investment. Confidence requires policies which balance supply and demand using believable methods with adequate allowance for the unexpected, reliance on diverse sources and locations, respect for our environment, sustain our individual freedoms and provide opportunities for economic mobility. Coal will play only a part, but an important part, in a multifaceted energy policy using numerous energy sources and systems, conservation techniques, and cooperating societal institutions. Today's extensive and challenging research and development provides the foundation for future technologies which will further resolve the environmental effects associated with coal.

Daines, N. H.↗

NASA NTRS2008

Lights Out Operations of a Space, Ground, Sensorweb

We have been operating an autonomous, integrated sensorweb linking numerous space and ground sensors in 24/7 operations since 2004. This sensorweb includes elements of space data acquisition (MODIS, GOES, and EO-1), space asset retasking (EO-1), integration of data acquired from ground sensor networks with on-demand ground processing of data into science products. These assets are being integrated using web service standards from the Open Geospatial Consortium. Future plans include extension to fixed and mobile surface and subsurface sea assets as part of the NSF's ORION Program.

Chien, Steve↗

NASA NTRS2023

Analysis of Strategic Conflict Management Approaches as Applied to Simulated UAM Operations

This report presents the results of a comparison analysis of candidate Strategic Conflict Management (SCM) strategies as applied to Urban Air Mobility (UAM) operations. The SCM strategies investigated included: no SCM, resource scheduling (RS), resource flow rates (FR), area-based flow rates (AR), and conflict detection and resolution (CR). The study evaluated each strategy against the same 3 levels of flight demand in a representative airspace construct for the Dallas/Fort Worth region. The study also accounted for different levels of uncertainty in operational planning and equivalent levels of trajectory following error. In the analysis, we compared the SCM strategies’ effectiveness in reducing the need for the tactical conflict management layer to act and looked at the metrics of unmitigated losses-of-separation (LOS), flight delays imposed by strategic planning, and throughput of the overall airspace. The study results indicated that the CR strategy was the most effective at reducing LOS and percentage of flights with LOS, even in the presence of trajectory error when uncertainty is accounted for in planning. Thus, if the objective is to reduce the number of actions that the tactical conflict management layer will have to take, in terms of conflicts that may need to be resolved, CR is the strategy to use. The FR strategy was found to be the worst at reducing LOS and percentage of flights with LOS. Thus, it is not very effective at reducing the actions required by a tactical conflict management layer. In the airspace tested, the demand was high enough to produce unacceptable levels of flight delay and reductions of throughput when the SCM strategies were implemented. This was especially evident at the higher levels of trajectory uncertainty and error. The need to account for expected levels of uncertainty becomes more and more important as the demand level increases and as the level of trajectory error increases. This is because the likelihood of flights with LOS increases as the density of operations increases and as the level of trajectory error increases. Accounting for uncertainty in the SCM strategies improves the strategy effectiveness with respect to LOS but increases delays and reduces throughput. Thus, there is a tradeoff between scalability and allowable levels of uncertainty. That is, we can implement an air traffic management construct that allows high levels of uncertainty, but we can expect that same system to have limits on scalability that may be evident even at small demand levels, such as those used in this study. Therefore, the results in this study indicate that an air traffic system should attempt to implement mechanisms appropriate for reducing uncertainty where possible in order to increase the chances for scalability. And this increased level of predictability of operations needs to be balanced with mechanisms for ensuring flexibility when operational conditions and plans need to change, even though those types of changes should be the exception rather than the rule under normal conditions. The study also introduced a trade space that could serve as a mechanism for selecting the appropriate SCM strategy in a trade-off between uncertainty and error, mean flight delay, and the LOS metrics (which this study equates to the potential for tactical conflict management actions). The optimal solution for a given airspace, demand level, and other factors, could likely be a combination of SCM strategies, although this study only compared the use of a single SCM strategy at a time. The CR strategy appeared to have the best opportunity for scalability by limiting the number of potential tactical actions to nearly zero.

Strategic Conflict Management↗

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↗