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From Rural to Urban Environments: Human/Systems Simulation Research for Low Altitude UAS Traffic Management (UTM)

This paper describes the human/systems simulation research within NASA's UAS (Unmanned Aircraft System) Traffic Management (UTM) project. The paper starts with a short description of the UTM project, then presents the UTM development schedule briefly, before leading into more detailed discussions of the simulation test beds current capabilities, as well as the ongoing and planned human/systems research activities.

unmanned aircraft systems↗

TCL3 UTM (UAS Traffic Management) Flight Tests, Airspace Operations Laboratory (AOL) Report

The Technology Capability Level-3 (TCL3) flight tests were conducted at six different test sites located across the USA from March to May of 2018. The campaign resulted in over 830 data collection flights using 28 different aircraft and involving 20 flight crews. Flights not only varied in duration, but also in the environments and terrains over which they flew. The TCL3 tests highlighted four different types of tests: three tests focused on Communication, Navigation and Surveillance (CNS); six tests focused on Sense and Avoid (SAA) technologies; six tests focused on USS Data and Information Exchange (DAT); and five tests focused on exploring fundamental Concepts of the project (CON). This document presents data collected during the TCL3 tests that informed the operator’s experiences—the quality of the unmanned aerial system (UAS) Service Supplier (USS) information that the operator was provided with, the usefulness of this information, and the usability of the automation, both while airborne and on the ground. It is intended to complement the reports written by the test sites and the quantitative reports and presentations of the UAS Traffic Management (UTM) project. With the goal of instructing what the minimum information requirements and/or best practices might be in TCL3 operations, the driving enquiry was: How do you get the information you need, when you need it, to successfully fly a UAS in UTM airspace? This enquiry touches on two requirements for displays, which are to provide adequate situation awareness (SA) and to share information through a USS. The six test sites participating in the TCL3 tests flew a subset of the 20 tests (outlined above), with most sites working on a subset of each of the four types: Communications, Navigation and Surveillance (CNS); DAT; CON; and Sense and Avoid (SAA). The, mainly qualitative, data addressed in this report was collected by the AOL (Airspace Operations Laboratory) both on-site and remotely for each test. The data consists of the contents of end-of-day debriefs, end-of-day surveys, observer notes, and flight test information, all submitted as part of the Data Management Plan (DMP).

Martin, Lynne↗

Small Unmanned Aerial System (UAS) Flight Testing of Enabling Vehicle Technologies for the UAS Traffic Management Project

Small unmanned aerial systems (sUAS) have been studied and results indicate that there is a large array of highly-beneficial applications. These applications are too numerous to list, but include search and rescue, fire spotting, precision agriculture, etc. to name a few. Typically sUAS vehicles weigh less than 55 pounds and will be performing flight operations in the presence of manned aircraft and other sUAS. Certain sUAS applications, such as package delivery, will include operations in the close proximity of the general public. The full benefit from sUAS is contingent upon the resolution of several technological areas to enable free and widespread use of these vehicles. Technological areas in question include, but are not limited to: autonomous sense and avoid and deconfliction of sUAS from other sUAS and manned aircraft, communications and interfaces between the vehicle and human operators, and high-reliability autonomous systems. The NASA UAS Traffic Management (UTM) project is endeavoring to develop a traffic management system and concept of operations for these types of vehicles. An extensive sUAS flight test effort was performed to partially address vehicle-related technological areas and to shape an understanding of future developmental and test efforts for vehicles intended to use the UTM traffic management system. The flight testing described herein had the following objectives: 1) Install and test Dedicated Short Range Communications (DSRC) systems developed for the automotive industry for potential sense and avoid sUAS applications; 2) Evaluate the use of cellular 4G systems to provide vehicle control; 3) Obtain high-resolution video imagery in support of image-based optical detection sense and avoid systems; 4) Acquire data in fixed-wing flight to support validation and maturation of an autonomous range containment system known as Safeguard in fixed-wing flight. A total of 53 flights were performed over 12 operational days at Beaver Dam Airpark in Elberon, VA. This work was sponsored by the UTM project that is part of the Aviation Operations and Safety Program (AOSP) at NASA.

Glaab, Louis J.↗

Incorporating UAS Traffic Management into Wildland Firefighting Operations: Initial Findings of Subject Matter Expert Interviews

Uncrewed Aircraft Systems (UASs) are being utilized throughout the disaster and emergency response domain, including in wildland firefighting operations. While UASs can offer safety benefits in comparison to crewed aircraft, such as removing the human pilot from the vehicle so that they are not exposed to the same risks and the ability to operate in low-visibility conditions, they are not without tradeoffs. For example, it can be challenging for UAS pilots (UASPs) to build situation awareness of the airspace in which their UAS is operating. In order to address some of the challenges associated with using UASs and provide greater assistance to the firefighters and incident personnel in the wildland firefighting environment, the National Aeronautics and Space Administration (NASA) launched the Advanced Capabilities for Emergency Response Operations (ACERO) project. Building on previous NASA research, ACERO will explore the implementation of a traffic management system in the wildland fire environment to enhance safety and support situation awareness. ACERO draws on the UAS Traffic Management (UTM) system previously demonstrated in an urban environment. However, a traffic management system implemented in the wildland fire environment is expected to look and function much differently in order to meet the unique needs of this domain. At the outset of the ACERO project, interviews were conducted with five UASPs who operate UASs at wildland fire incidents. The interviews focused on exploring UASPs’ initial insights about the application of a traffic management system in wildland firefighting and understanding the unique needs of this environment. The UASPs discussed a range of topics including, the shape, size, and organization of UAS operations in the wildland fire environment, information needs for a user interface, such as traffic and map information, an alerting function when other traffic nears their operation area, and the importance of conformance monitoring. The UASPs also discussed their willingness to share operational information to support safety. In this paper, we describe the foundational work upon which ACERO will build and summarize the information and insights gathered during the UASP interviews, some of which have already informed the development of the ACERO work.

Uncrewed Aircraft System (UAS)↗

Incorporating UAS Traffic Management into Wildland Firefighting Operations: Initial Findings of Subject Matter Expert Interviews

Uncrewed Aircraft Systems (UASs) are being utilized throughout the disaster and emergency response domain, including in wildland firefighting operations. While UASs can offer safety benefits in comparison to crewed aircraft, such as removing the human pilot from the vehicle so that they are not exposed to the same risks and the ability to operate in low-visibility conditions, they are not without tradeoffs. For example, it can be challenging for UAS pilots (UASPs) to build situation awareness of the airspace in which their UAS is operating. In order to address some of the challenges associated with using UASs and provide greater assistance to the firefighters and incident personnel in the wildland firefighting environment, the National Aeronautics and Space Administration (NASA) launched the Advanced Capabilities for Emergency Response Operations (ACERO) project. Building on previous NASA research, ACERO will explore the implementation of a traffic management system in the wildland fire environment to enhance safety and support situation awareness. ACERO draws on the UAS Traffic Management (UTM) system previously demonstrated in an urban environment. However, a traffic management system implemented in the wildland fire environment is expected to look and function much differently in order to meet the unique needs of this domain. At the outset of the ACERO project, interviews were conducted with five UASPs who operate UASs at wildland fire incidents. The interviews focused on exploring UASPs’ initial insights about the application of a traffic management system in wildland firefighting and understanding the unique needs of this environment. The UASPs discussed a range of topics including, the shape, size, and organization of UAS operations in the wildland fire environment, information needs for a user interface, such as traffic and map information, an alerting function when other traffic nears their operation area, and the importance of conformance monitoring. The UASPs also discussed their willingness to share operational information to support safety. In this presentation, we describe the foundational work upon which ACERO will build and summarize the information and insights gathered during the UASP interviews, some of which have already informed the development of the ACERO work.

Uncrewed Aircraft Systems (UAS)↗

Developing and Testing Two Interfaces for Supplemental Data Service Provider (SDSP) Tools to Support UAS Traffic Management (UTM)

Researchers conducted a usability study using two graphical user interfaces (GUIs) to explore how individuals interpret and interact with different preflight information displays, and to inform the development of Uncrewed Aircraft System (UAS) preflight planning predictive support tools to assess and mitigate flight hazards and risks. A series of preflight risk-assessment tasks were developed to evaluate participant performance using the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD) and the Human Automation Team Interface System (HATIS) GUIs. Participants were trained to use both interfaces and their performance was evaluated. These evaluations focused on participants’ preflight planning activities. Objective data on performance tasks across different scenarios involving multi-UASs, as well as self-reports of interactions and subjective experiences using the GUIs were collected. Scores on the system usability scale (SUS) and on a simple task set were examined, as well as user feedback on open-ended questions, to inform development and identify potential improvements to the interfaces.

sUAAV interfaces↗

Developing and Testing Two Interfaces for Supplemental Data Service Provider (SDSP) Tools to Support UAS Traffic Management (UTM)

Researchers conducted a usability study using two graphical user interfaces (GUIs) to explore how individuals interpret and interact with different preflight information displays, and to inform the development of Uncrewed Aircraft System (UAS) preflight planning predictive support tools to assess and mitigate flight hazards and risks. A series of preflight risk-assessment tasks were developed to evaluate participant performance using the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD) and the Human Automation Team Interface System (HATIS) GUIs. Participants were trained to use both interfaces and their performance was evaluated. These evaluations focused on participants’ preflight planning activities. Objective data on performance tasks across different scenarios involving multi-UASs, as well as self-reports of interactions and subjective experiences using the GUIs were collected. Scores on the system usability scale (SUS) and on a simple task set were examined, as well as user feedback on open-ended questions, to inform development and identify potential improvements to the interfaces.

sUAAV interfaces↗

Unmanned Aircraft System (UAS) Traffic Management (UTM): Enabling Civilian Low-Altitude Airspace and Unmanned Aerial System Operations

Just a year ago we laid out the UTM challenges and NASA's proposed solutions. During the past year NASA's goal continues to be to conduct research, development and testing to identify airspace operations requirements to enable large-scale visual and beyond visual line-of-sight UAS operations in the low-altitude airspace. Significant progress has been made, and NASA is continuing to move forward.

UTM↗

Evaluation of Early Ground Control Station Configurations for Interacting with a UAS Traffic Management (UTM) System

The purpose of this paper is to report on a human factors evaluation of ground control station design concepts for interacting with an unmanned traffic management system. The data collected for this paper comes from recent field tests for NASA's Unmanned Traffic Management (UTM) project, and covers the following topics; workload, situation awareness, as well as flight crew communication, coordination, and procedures. The goal of this evaluation was to determine if the various software implementations for interacting with the UTM system can be described and classified into design concepts to provide guidance for the development of future UTM interfaces. We begin with a brief description of NASA's UTM project, followed by a description of the test range configuration related to a second development phase. We identified (post hoc) two classes in which the ground control stations could be grouped. This grouping was based on level of display integration. The analysis was exploratory and informal. It was conducted to compare ground stations across those two classes and against the aforementioned topics. Herein, we discuss the results.

unmanned traffic management↗

Real-Time Risk Assessment Framework for Unmanned Aircraft System (UAS) Traffic Management (UTM)

The new Federal Aviation Administration (FAA) Small Unmanned Aircraft rule (Part 107) marks the first national regulations for commercial operation of small unmanned aircraft systems (sUAS) under 55 pounds within the National Airspace System (NAS). Although sUAS flights may not be performed beyond visual line-of-sight or over non- participant structures and people, safety of sUAS operations must still be maintained and tracked at all times. Moreover, future safety-critical operation of sUAS (e.g., for package delivery) are already being conceived and tested. NASA's Unmanned Aircraft System Trac Management (UTM) concept aims to facilitate the safe use of low-altitude airspace for sUAS operations. This paper introduces the UTM Risk Assessment Framework (URAF) which was developed to provide real-time safety evaluation and tracking capability within the UTM concept. The URAF uses Bayesian Belief Networks (BBNs) to propagate off -nominal condition probabilities based on real-time component failure indicators. This information is then used to assess the risk to people on the ground by calculating the potential impact area and the effects of the impact. The visual representation of the expected area of impact and the nominal risk level can assist operators and controllers with dynamic trajectory planning and execution. The URAF was applied to a case study to illustrate the concept.

Ancel, Ersin↗

FAA/NASA UAS Traffic Management Pilot Program (UPP)

NASA Ames is leading ATM R&D organization. NASA started working on UTM in 2012, it's come a long way primarily due to close relationship with FAA and industry. We have a research transition team between FAA and NASA for UTM. We have a few other RTTs as well. UTM is a great example of collaborative innovation, and now it's reaching very exciting stage of UTM Pilot Project (UPP). NASA is supporting FAA and industry to make the UPP most productive and successful.

Johnson, Ronald D.↗

Analysis of At-Altitude LTE Power Spectra for C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration’s (NASA) Unmanned Aircraft Systems Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude small Unmanned Aerial Systems (sUAS, also known as drones) operations. This paper presents results of work completed in the paper [1] presented at the 2018 ICNS conference where proposed approaches were explored for evaluating and analyzing sUAS Command and Control (C2) links based on commercial cellular networks. This paper focuses on the UTM Project’s Technology Capability Level 3 (TCL-3) test results which address the communications portion identified within the same paper. A software defined radio (SDR) was flown as a sUAS payload to capture received signal spectrum in Long Term Evolution (LTE) frequency bands of interest. The purpose was to measure the RF environment at UTM altitudes to characterize the interference potential. The SDR payload was flown at various stationary altitudes where the LTE over-the-air complex (I/Q) samples were captured by the SDR and later post-processed. The SDR received inputs through an omnidirectional antenna. The complex samples captured were an aggregate of transmissions received from all line-of-sight (LOS) towers within the geographic area for the specific radio frequency bandwidth the SDR is programmed to capture. Using this approach, the complex samples captured do not distinguish between the various eNodeB's (Long Term Evolution (LTE) transmitting towers). The complex samples were post processed via a Discrete Fourier Transform (DFT) algorithm to view the captured spectrum along with the power levels across the captured LTE bandwidth. This SDR payload process of capturing complex samples was done at two different regions within the US: 1) NASA's Ames Research Center (ARC) in Moffett Field, CA, and 2) Griffiss Airfield in Rome, NY. The data capture at the ARC site was done at two physical locations within the Ames campus where many stationary altitude captures where done as high as 800 ft. above ground level (AGL). The data captured at the Griffiss Airport (also known as the NY Corridor Site) were acquired at one location with three specific stationary altitude levels – {Ground Level (GL), 300 ft., and 400 ft.}. The LTE spectrum power levels were captured for two LTE carriers, AT&T and Verizon, at both sites where their respective spectra and power levels were measured and compared at various altitudes. The overall results show that there is an increase in LTE spectrum power levels at higher altitudes for drones. A detailed analysis of this data and conclusions drawn from the results are presented in this paper.

Kerczewski, Robert J.↗

Unmanned Autonomous Systems (UAS) Traffic Management

This presentation is for the Plenary Session: "Unmanned Traffic Management (UTM) and the Future of Unmanned Systems in Urban Airspace" at the ASCE flagship 2019 International Conference on Transportation and Development, "Engineering Smart Mobility for the Smart City", June 9-12, 2019. The Panel is at 8:00 am on Wednesday, June 12 and moderated by Brent Ingraham (DOD). This presentation supplements Dr. Kopardekar's short introduction on how NASA is developing an Unmanned Traffic Management system and how this UTM will change the future of shared airspace.

Kopardekar, Parimal H.↗