Search NASA⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20230016650

Sim to Flight: Evaluating Flight Path Management Automation in High Density Urban Environments

Bryan A. Barrows·Mark G. Ballin·Terique L. Barney·Stewart L. Nelson·Matthew C. Underwood·David J. Wing
View original source ↗Export metadata ↓

Abstract

Combined simulation and flight testing enable the study of single- and multi-aircraft performance of onboard automation systems for dynamic flight path management (FPM). The National Aeronautics and Space Administration (NASA) is investigating system performance and functional capabilities of such automation for immersion into complex, high density, future operations such as Urban Air Mobility (UAM). This paper provides an overview of a series of interdependent sim-to-flight research activities involving large-scale batch simulations, human-in-the-loop verification, and flight-test validation of a research prototype FPM automation system. Together, they significantly contributed to a functional assessment of FPM automation functionality in a live-virtual-constructive (LVC) operating environment characterized by two live aircraft and hundreds of virtual aircraft interacting in a modeled complex urban airspace. Initial simulation and flight test results, future work, and conclusions are presented.

Explore related subjects

Advanced Air MobilityFlight Path ManagementUrban Air MobilityNational Campaign

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bryan A. Barrows, Mark G. Ballin, Terique L. Barney, Stewart L. Nelson, Matthew C. Underwood, David J. Wing. Sim to Flight: Evaluating Flight Path Management Automation in High Density Urban Environments. https://ntrs.nasa.gov/citations/20230016650

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2023

Ch. 12. A Theoretical Approach to Management of Limited Attentional Resources to Support the m:N Operation in Advanced Air Mobility Ecosystem

Advanced air mobility (AAM) technologies incorporate increasingly autonomous systems that allow fully remote, independent, and intelligent operation of air vehicles to support the transportation of goods and passengers within and across urban and rural areas. With a myriad of automated technologies enabling the AAM ecosystem, the human operator’s role will likely be a passive supervisory monitor of the air vehicles, involving increasingly fewer humans (m) that manage many more autonomous systems (N), or m:N operations. Unfortunately, the human performance literature suggests that human operators will exhibit poor supervision of numerous autonomous agents due to the limits of attentional resources in the operators. In the general human information-processing model, a human operator exercises a limited pool of attentional resources to engage various information-processing stages including detecting, perceiving, comprehending, and predicting objects around them. Yamani and Horrey (2018) expanded the human information-processing model to characterize a tradeoff between information-processing demand and resource relief that automation brings in the context of automated driving. In their model, a driver interacting with an automated driving system is assumed to reallocate resources “freed” by automation to support other information-processing stages required for successful task performance. A future AAM ecosystem enabled by an orchestration of advanced automated systems, however, requires a single operator to interact with more than one air vehicle with varying levels and degrees of automated systems, making the traditional framework of human-automation interaction insufficient. To address this gap, we provide a review of the literature on situation assessment and trust, two constructs identified as critical for a fuller understanding of intimate and intricate interactions between a human operator and multiple air vehicles equipped with increasingly autonomous systems. Then, we propose an expansion of Yamani and Horrey’s (2018) model to motivate systematic research on the human operator’s role, identify factors that influence resource allocation and guide human-centered design of an interface supporting the m:N operation in the AAM environment.

Advanced Air Mobility↗
NASA NTRS2023

Acoustics Technical Working Group and UAM Noise Working Group Proceedings

The NASA Acoustics Technical Working Group Meeting originally started as a program planning meeting in 1992 and has grown through the years. The purpose of these biannual meetings is to foster communication and collaboration among NASA researchers and their university, industry, and government colleagues on activities and work of current and future mutual interest. The NASA-led Urban Air Mobility (UAM) Noise Working Group (UNWG) Meeting began in 2018 as a one-day meeting immediately following the Acoustics Technical Working Group Meeting. The UNWG utilizes four subgroups that conduct regular meetings throughout the year to focus on challenges facing UAM vehicles for community noise and acceptance. The four subgroups coordinate research for development of noise prediction tools/noise reduction technologies, ground and flight test methods, human response and metrics, and regulations and policy (led by the FAA). This work is a compilation of the presentations given at ATWG/UNWG Fall 2022 held in person and via Teams at NASA Glenn Research Center. All NASA content was previously submitted through STRIVES for public presentation. This is merely a compilation. Non-NASA content has permission to distribute. Slide 208 video is included in the Available Downloads as Medial.MOV.

Advanced Air Mobility↗