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NASA NTRSDate not supplied

sUAS Ground Control Station Capabilities Impact on Fleet Management

Future Small Uncrewed Aerial Systems (sUAS) missions will require multiple operators to collaborate and manage large fleets of highly automated vehicles. It is critical that these operators maintain the necessary situational awareness to modify vehicle missions if/when unexpected situations arise in the operating environment. It has been suggested that highly automated vehicle capabilities can lead to reducing the capabilities given to operators to modify/direct vehicle missions. This paper explores various Ground Control Station (GCS) capabilities configurations and their impact on sUAS fleet management. Results show that a GCS with a combination of manual and automated capabilities allowed participants to make more effective decisions while maintaining workload and response times similar to that of a GCS with only automated capabilities.

sUAS↗

NASA NTRSDate not supplied

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (AAM) (i.e. urban and rural unmanned aircraft systems) ecosystem, the NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV) to prototype and study the effectiveness AAM capabilities under various operational contexts. HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called the Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with the FMI to identify optimal approaches for displaying information to human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a remotely controlled vehicle completed a takeoff, active flight, and landing sequence while simulated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self- reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users suggested customizable interfaces to accommodate information display preferences, and the ability to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could serve to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

Fleet manager↗

NASA NTRSDate not supplied

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (i.e. urban and rural unmanned aircraft systems) ecosystem, NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV). HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with FMI to identify optimal approaches for displaying information for human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a controlled vehicle completed a takeoff, active flight, and landing sequence while automated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self-reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users would like greater configurability of the interface based on their personal information requirements, and they would like the opportunity to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could be introduced as a potential way to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

vertiplex↗

NASA NTRSDate not supplied

Progressive Development of Fleet Management Capabilities for a High Density Vertiplex Environment

The High Density Vertiplex (HDV) Sub-Project, as part of NASA’s Advanced Air Mobility (AAM) Project, has been developing a reference automation architecture with a far-term view of scalable, high-density operations in and around vertiport terminal areas. One of the components of that architecture under development has been focused on fleet management capabilities to support the management of multiple AAM operations from a supervisory role of a fleet manager. This capability relies on connectivity and information exchanges with other services for airspace and vertiport management as well as with flight crews responsible for operation execution. This paper will present this capability with a focus on its user interface developments as well as its integration into the simulation and flight testing performed as part of the HDV research roadmap.

high density vertiport↗

NASA NTRSDate not supplied

Progressive Development of Fleet Management Capabilities for a High Density Vertiplex Environment

AAM↗

DOE OSTI2024

Electric Vehicle Fire Primer for Fleet Managers

The U.S. Department of Energy's Vehicle Technologies Office provides project assistance through Clean Cities, technical expertise, and funding to help stake-holders implement alternative fuels and electric vehicles (EVs). Fleet managers considering EVs can learn about the potential for EV fires and measures to help reduce fire risk.

ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

Qualitative Data Coding of User Experience with an Urban Air Mobility Fleet Manager Interface

The NASA Aeronautics Research Mission Directorate created the High Density Vertiplex (HDV) project to integrate and evaluate a prototype Urban Air Mobility (UAM) ecosystem. Part of the HDV testing environment included a prototype operator user interface called the Fleet Manager Interface (FMI). In 2023, HDV conducted flight testing with the FMI during which a user experience (UX) study was performed to assess the quality of UX and elicit design recommendations. As a result, a large database of open-ended, qualitative responses was generated and then coded using a new qualitative data coding technique called Directive String Coding, which used a blended coding approach to generate actionable heuristics that stakeholders (e.g., researchers, UI designers, software developers) could use to answer specific research questions and make future design decisions. The key themes that arose from the coded responses showed that the UX was pleasant, system notifications should be more salient, and information across multiple screens should be integrated into a central display. As the Fleet Manger operational role is still being defined, it is vital to increase our understanding of the tools and capabilities needed for such a role. The results from HDV work will eventually feed into standards for vertiport operations that will enable safe and scalable UAM operations in the United States.

high density vertiplex↗

NASA NTRSDate not supplied

Qualitative Data Coding of User Experience with an Urban Air Mobility Fleet Manager Interface

high density veriplex↗

NASA NTRSDate not supplied

Urban Air Mobility Fleet Manager Gap Analysis and System Design

NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in re-search to facilitate the introduction of air taxis into the US National Airspace System. Given the history of conventional aircraft operations, it is clear that dispatcher support will be required for UAM. This paper presents a gap analysis, system requirements, and a workstation design concept for the UAM dispatcher or Fleet Manager (FM) position. The gap analysis focuses on the differences be-tween the tasks of the airline dispatcher and those projected for the FM. FM system capabilities and data requirements are then presented as foundations for soft-ware development. An initial user interface concept is provided. The FM software uses a single, large display. The system supports prediction, monitoring, and task execution. This paper is intended to support FM software design for future air taxi systems.

Richard Mogford↗

NASA NTRS1995

MSAT wide-area fleet management: End-user requirements and applications

MSAT (Mobile SATellite) Services will become a reality in North America in 1995. MSAT will provide wide-area voice, data and fax services to land, marine and aeronautical mobile users anywhere in North America including 200 nautical miles off the coasts and into the Arctic waters. MSAT will also convey GPS position information from mobiles to dispatch centers. One broad application of MSAT is Wide Area Fleet Management (WAFM). This paper defines WAFM, outlines end-user requirements and identifies potential applications of MSAT WAFM. The paper draws from information obtained in several preMSAT WAFM field trials in land, marine and aeronautical mobile environments. The paper concludes with an outline of the potential benefits of MSAT WAFM.

Pedersen, Allister↗

NASA NTRS2020

UAM Fleet Manager Gap Analysis

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

Mogford, Richard↗

NASA NTRS2019

Urban Air Mobility Fleet Manager Gap Analysis and System Design

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

Mogford, Richard↗

DOE OSTI2025

Optimized V1G and V2G Electric Vehicle Fleet Management and Grid Transaction at Marine Corps Air Station Miramar in San Diego, CA

The overall technical goal of the project was to demonstrate an all-electric bi-directional non-tactical fleet at Marine Corps Air Station (MCAS) Miramar that was integrated and controlled with other distributed energy resources (DERs) (i.e., PV, stationary battery, and building loads) to provide resilience to critical electric loads in the event of grid outages, to minimize charging costs, and to provide economic energy resources to electricity markets. In this project, the specific, technical objectives were: 1. Demonstrate that bi-directional electric vehicles can provide critical complementary services to fixed storage batteries in microgrid applications while performing function as non-tactical vehicles. 2. Demonstrate participation of bi-directional (V2G) and unidirectional (V1G) PEVs for demand management and minimization of charging costs. 3. Demonstrate integration of multiple DERs for grid service participation. US Marine Corps Air Station (MCAS) Miramar in San Diego was the site of this electric vehicle-to-microgrid-utility grid test and demonstration project. Existing microgrid assets in this study included (1) a public works building; (2) a 30-kW rooftop photovoltaic (PV) system and (3) a separate 250 kW carport PV system. In this project, six bi-directional V2G vans were located at the MCAS Miramar’s showcase building-scale microgrid to develop and test technical capabilities that V2G can provide in microgrid applications (e.g., cost reduction and resiliency). These resources provided aggregated demand management and simulated participation in current retail DR programs. The vehicles used in this demonstration were selected because they provided functionality that MCAS Miramar needed, 15 passenger transport and facilities work cargo carrying capacity, and bi-directional charging capability that the research project required. All vehicles in this study were manufactured and distributed by VIA Motors, Inc. There were six vehicles total and each was VIA’s VTRUX eREV V2G model, a modified General Motors Chevrolet 2500 2WD van. Three of the vans were configured as passenger vans and the other three were configured as cargo vans. Each van had an on-board bi-direcrtional inverter/charger, Bel Power Solutions model 350INVCHGT150-120-240-8G nominally rated at +/-15 kW. The VIA van’s charging connector follows the J1772 charging protocol. The bi-directional EVSEs demonstrated in this study were manufactured by Coritech, Inc. Each VGI-80-AC charging station enabled enhanced V2G charging capability to a Clipper Creek CS-100 charging module. The enhanced capabilities included ethernet communication following the SEP2.0 protocol with a distributed energy resource function set and an operator screen displaying real-time SOC, voltage, and current. The VGI-80-AC charging stations are classified as level 2 with a maximum current output of 80 A or effectively 19 kW. The VIA van’s onboard charger limited the charging and discharging power to 15 kW in each direction. A control computer was installed in the EWOC and connected to an existing monitor. The V2G control communication network was a completely stand-alone closed system that did not have any connection to any other networks on the base. A cybersecure remote communication connection was created with a cellular modem, firewall hardware, and a virtual private network configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) subproject aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-TheLoop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and MultiAircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

Advanced Air Mobility↗

NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) sub- project aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-The- Loop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and Multi- Aircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

advanced air mobility↗

DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2021

m:N and Human Autonomy Teaming Concepts for High Density Vertiport Operations

This report focuses on the role of the Fleet Manager (FM) and, in particular, the ways in which automation could support their position as they manage multiple aircraft and operators in a highly dynamic, advanced air mobility (e.g., air taxi) environment, specifically "high-density vertiport" (HDV) regions. Similar to terminal area operations for traditional aviation, operations involving HDVs will need to be highly structured while also remaining resilient to the various contingencies that can happen in that environment. The role of the FM is consistent with an “m:N” architecture, where “m” number of operators cooperatively manage “N” number of vehicles (where “N” is always larger than “m”). In such a paradigm it is critical to provide the operator with the tools and information necessary to manage their fleet safely and navigate the known pitfalls with highly automated, complex systems (e.g., brittleness, insufficient situation awareness, skill degradation). As the field of m:N has expanded as an area of study, a set of higher-level automation concepts have emerged—namely “plays,” “working agreements,” and “human-autonomy teaming” (HAT)—that could support operators in this new role.

human autonomy teaming↗

NASA NTRSDate not supplied

Development of a Safety Hazards Risk Assessment Tool for Uncrewed Aircraft System Traffic Management during Preflight Planning

Tremendous growth in the uncrewed and remotely piloted vehicle market is expected in low-altitude, uncontrolled airspace, resulting in potential decreases in safety without systems that support monitoring, assessing, and mitigating risk. At NASA, the System-Wide Safety (SWS) project has been developing a suite of data-driven tools to predict hazards so that the potential risks that these hazards pose can be mitigated. Services to predict various hazards have been developed, including battery capacity, proximity to static obstacles, population risks, global positioning system signal strength, radio frequency spectrum interference risk, and vertiport congestion. These services can monitor hazards along a flight path and if any risks posed by these hazards exceed a threshold, the uncrewed aircraft system (UAS) fleet manager can be alerted to mitigate the risk by modifying the flight path, changing the scheduled departure or arrival times, and/or diverting the vehicle to an alternate vertiport. These services were originally developed to monitor and assess risks during flight, but they have been adapted to assess hazard risks prior to departure so that a fleet manager can evaluate the potential risks for a fleet of UAS along their planned flight paths. These services have been integrated into a prototype tool called the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD), developed at NASA Ames Research Center. The tool consists of a dashboard which provides a comprehensive overview for a number of risks and a map display that shows the details of the hazards along each flight’s path. Based on the findings from three previous studies, the SDSP-CD has been updated with new design elements and functions. In this paper, we describe lessons learned from the previous studies, changes made to the interface, and the feedback received during a follow-up usability study. Overall, participants reported that there is a substantial benefit of having a fleet manager use a consolidated dashboard to assess hazards for the vehicles in their fleet and to provide situational awareness to potential risks so that they can be mitigated prior to flight. Once the SDSP-CD matures, it will need to be integrated into flight and mission planning tools. Some initial thoughts on how this integration should be accomplished are shared in this paper. Finally, the functional differences between preflight vs. in-flight risk assessment and the differences in fleet manager vs. UAS pilot roles that may require different information and user interactions are discussed.

preflight↗