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29 records · Page 2

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↗

Lightweight Surveillance and Target Acquisition Radar Characterization for High Density Vertiplex Beyond Visual Line of Sight Operations

Abstract- with the growth of the National Aeronautics and Space Administration (NASA) National Campaign, it is becoming increasingly important for government and enforcement agencies to be able to monitor and safely track urban air traffic that will take place in the coming years. The performance of the Lightweight Surveillance and Target Acquisition Radar (LSTAR) is investigated and statistically characterized. The compact LSTAR is mounted on a building at NASA Langley Research Center (LaRC) and operated to track a SR-22 aircraft. Performance data of of the LSTAR tracking is presented by comparing the LSTAR-tracked flight against the on-board flight records and statistical characteristics are presented. Implications of findings to operations within High Density Vertiplex (HDV) at LaRC are discussed. The LSTAR ultimately proves to be a compact method to safely track and monitor small aircraft and other unmanned aerial vehicles.

Nicholas Gaug↗

Lightweight Surveillance and Target Acquisition Radar Characterization For High Density Vertiplex Beyond Visual Line of Sight Operations

With the growth of the National Aeronautics and Space Administration (NASA) National Campaign, it is becoming increasingly important for government and enforcement agencies to be able to monitor and safely track urban air traffic that will take place in the coming years. The performance of the Lightweight Surveillance and Target Acquisition Radar (LSTAR) is investigated and statistically characterized. The compact LSTAR is mounted on a building at NASA Langley Research Center (LaRC) and operated to track a SR-22 aircraft. Performance data of the LSTAR tracking is presented by comparing the LSTAR-tracked flight against the onboard flight records and statistical characteristics are presented. Implications of findings to operations within High Density Vertiplex (HDV) at LaRC are discussed. The LSTAR ultimately proves to be a compact method to safely track and monitor small aircraft and other unmanned aerial vehicles.

Nicholas M. Gaug↗

MBSE Execution of Scalable Autonomous Operations for a High Density Vertiplex

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE) and NASA SE processes were executed via MBSE using MagicDraw. Since the adoption of MBSE and utilization of MagicDraw, the systems engineering team has made tremendous strides in each pillar of MBSE including, requirements, behavior, and structure. Scalable Autonomous Operations (SAO) was a stage in the development of the High Density Vertiplex focusing on the autonomous terminal operations of a vertiport with sUAS aircraft. MBSE served the systems engineering team to document and verify the physical architecture and capture a logical architecture of SAO for distribution to the AAM community. This paper will detail methodologies that were created to successfully execute NASA SE processes via MBSE in the SAO stage as well as highlight challenges and lessons learned.

Demetrios Katsaduros↗

Advancements in Remote Ground Control Station Operator Pilot in Command Training Program for Beyond Visual Line of Sight Flight Operations

The training program for a Remote Ground Control Station Operator Pilot in Command (R-GCSO PIC) at NASA Langley Research Center marks a pivotal evolution in preparing operators for Beyond Visual Line of Sight (BVLOS) operations. This program, developed within the Advanced Air Mobility (AAM) project High Density Vertiplex (HDV) subproject, was crafted to bridge the gap between traditional Ground Control Station Operators (GCSO) and R-GCSO PICs, focusing on uncrewed aircraft systems (UAS). It encompassed extensive theoretical and practical training, including hands-on experience with advanced simulators and live flight operations, while ensuring a deep understanding of BVLOS complexities. The training leveraged NASA technologies like the MPATH (Measuring Performance for Autonomy Teaming with Humans) ground control station software and incorporated human factors principles to enhance operational readiness. This paper details the program's development, execution, and the critical insights gained, emphasizing the necessity of continuous adaptation in training methodologies to meet the evolving demands of UAS operations in the National Airspace System.

Ground control station operator↗

High Density Vertiplex: Scalable Autonomous Operations Flight Test

The NASA High Density Vertiport project has completed a multi-aircraft flight test of a scalable autonomous vertiport prototype system. These tests included end to end system integration testing of hardware and software, operational procedure testing of defined roles and responsibilities within a vertiport environment, and human factors data collection. This paper provides an overview of the flight test setup , scenarios, and summary results.

AAM↗