Lessons Learned: Using UTM Paradigm for Urban Air Mobility

Savita A Verma; Spencer C Monheim; Kushal A Moolchandani; Priyank Pradeep; Annie W Cheng; David P Thipphavong; Victoria L Dulchinos; Heather Arneson; Todd A Lauderdale; Christabelle S Bosson; Eric R Mueller; Bogu Wei

NASA NTRS · 20205004165

Lessons Learned: Using UTM Paradigm for Urban Air Mobility

Savita A Verma·Spencer C Monheim·Kushal A Moolchandani·Priyank Pradeep·Annie W Cheng·David P Thipphavong·Victoria L Dulchinos·Heather Arneson·Todd A Lauderdale·Christabelle S Bosson·Eric R Mueller·Bogu Wei

View original source ↗Export metadata ↓

Abstract

Urban Air Mobility (UAM) aims to reduce congestion on the roads and highways by offering air taxi as an alternative to driving on surface roads. Integration of UAM operations in the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. A simulation was performed in collaboration with Uber Technologies Inc to investigate if NASA’s UTM architecture and its implementation as demonstrated in the 2019 UTM field tests were extensible for UAM operations, and if the data exchange between multiple operators as planned under UTM were adequate for UAM operations in the shared airspace. In order to explore these research questions, three Use Cases were defined to investigate different airspace management challenges. This paper will describe the lessons learned from exercising the uses cases and the airspace management services including scheduling and separation developed to facilitate initial UAM operations.

Explore related subjects

Urban Air Mobility UAM Unmanned Aviation Systems Traffic Management UTM

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Savita A Verma, Spencer C Monheim, Kushal A Moolchandani, Priyank Pradeep, Annie W Cheng, David P Thipphavong, Victoria L Dulchinos, Heather Arneson, Todd A Lauderdale, Christabelle S Bosson, Eric R Mueller, Bogu Wei. 2020-10-16. Lessons Learned: Using UTM Paradigm for Urban Air Mobility. https://ntrs.nasa.gov/citations/20205004165

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

KEEP EXPLORING

Related reports

NASA NTRS2024

Toward a Psychoacoustic Annoyance Model for Urban Air Mobility Vehicle Noise

A psychoacoustic test was performed to obtain annoyance responses to noise from a quadrotor Urban Air Mobility (UAM) vehicle to aid in the development of a model of annoyance to UAM vehicle noise. Previous analysis of that test concluded that a psychoacoustic annoyance (PA) model, including the effects of loudness, sharpness, fluctuation strength and roughness, correlated well with the collected annoyance responses. This motivated the assessment of other PA models available in the literature, as well as the development of a new PA model based on the previously collected annoyance responses to UAM noise. To build the PA model for UAM noise, annoyance ratings to individual sounds and annoyance comparisons between pairs of sounds are first combined into a latent annoyance scale that has a correlation coefficient of 0.98 with the raw responses and that is based on just-noticeable-differences (JNDs) in annoyance. Examples for two sounds that differ in annoyance by 1 JND show when there is 75% agreement about which sound is more annoying. This latent annoyance (JND) scale also gives insight into the interplay of various perceptual components, such as overall loudness, temporal effects and spectral effects. The proposed PA model for UAM noise is fit to the latent annoyance scale, includes the sound quality effects mentioned above, as well as a term for tonality, and offers a step forward in the prediction of annoyance to UAM vehicle noise.

Urban Air Mobility↗

NASA NTRS2023

A Blockchain Case Study for Urban Air Mobility Operational Intent

To realize the potential of Urban Air Mobility (UAM), an assurance of cybersecurity is critical for public acceptance. UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) aircraft to overcome increasing surface congestion. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. The intent of this work is to leverage a permissioned blockchain to simulate secure data exchange and storage for the UAM operational intent use case. In this case study, two vehicle operators are operating in the same airspace. Their intent is to fly vehicles that land at a shared vertiport, securely.

Urban Air Mobility↗

NASA NTRS2023

Pilots’ Perspectives on Urban Air Mobility Safety Challenges and Potential Solutions

As electric vertical takeoff and landing air taxis make their way to urban airspace operations within the United States National Airspace System, many research efforts are underway to identify and understand pertinent issues needed to support the influx of new, passenger-carrying, air vehicles over highly dense, urban communities. The primary focus of the Urban Air Mobility (UAM) Pilot/Provider of Services for UAM Information Exchange and Contingency Airspace Management Procedures study was to gather subjective data from subject matter experts concerning current-day airspace operations to identify potential gaps and improvements needed to support and sustain near-term UAM operations. These potential gaps and improvements will form the foundation for the development of initial information exchange requirements between the on-board pilot in command and other key entities. This paper focuses on the in-flight incapacitated pilot scenario from Phase I of the study, which gathered data from helicopter and general aviation fixed-wing pilots.

Urban Air Mobility↗