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At least 703 records · Page 39

Urban Area Unmanned Aerial Systems Sensor Capabilities for Ensuring Ground Hazards Safety

Unmanned aerial systems (UASs) in urban areas can pose significant safety risks to dynamic ground objects (DGOs) such as people, pets, and bikes; especially for off-nominal emergency traverses and landings. This paper will examine a framework for evaluating the UAS safety benefits which can be achieved by classifying DGO hazards, modeling their behavior, and assigning collision costs. DGOs are assumed to be any ground objects which are either moving or capable of moving. Safety benefits will be assessed by analyzing metrics computed from UAS and DGO trajectories which take into account intent and uncertainties. This paper will establish the theoretical relationships mapping these trajectories and DGO classifications to safety levels. Sensor capabilities will be mapped to DGO trajectory uncertainties, so that safety can be directly estimated from the sensor specifications for a given UAS trajectory.

Bouyssounouse, Xavier↗

Overview of the PLEXIL Plan Execution Technology and its Applications in Autonomous Piloting Projects at NASA

Automated planning is a key Artificial Intelligence technology enabling Unmanned Aerial Systems (UAS) and the eminent reality of Urban Air Mobility (UAM). It produces plans, which formalize procedures often performed by humans. Plans differ from other kinds of computer programs in their ability to react and interact with a dynamically changing environment. Aviation plans must encode the procedural knowledge, reasoning capability, and capacity for multi-tasking held by competent human pilots. Correct execution of these plans (performed by software called an executive) in the dynamic airspace environment is vital to the success of each automated flight, and the safety of the vehicle and all things in its path. In the early 2000s NASA developed a plan representation language and executive called PLEXIL (Plan Execution Interchange Language) that has successfully been applied in several NASA aviation and UAS projects. Autonomy Operating System (AOS), Cockpit Hierarchical Automated Planning and Execution (CHAP-E), and ICAROUS are all projects that have used PLEXIL to help encode and automatically execute flight procedures, some normally performed by human pilots. AOS also automates a subset of pilot/Air Traffic Control communication towards enabling UAS entry into the National Airspace. PLEXIL has been open-source software since 2008 and has seen usage in a wide range of prototypical autonomy applications in academia, government, and industry. In this presentation, we describe PLEXIL and highlight its significant accomplishments in the aviation domain.

Dalal, Michael↗

Small Unmanned Aircraft System Off Nominal Operations Reporting System Unmanned Aircraft System: Traffic Management Technical Capability Level 4 Implementation, Data Collection and Analysis

NASA performed research and development of technologies and requirements for traffic management of small Unmanned Aircraft Systems (UAS). In this effort, a small UAS off-nominal situation reporting system was developed to capture information from off-nominal situations to understand their nature and reduce occurrences. This Technical Memorandum (TM) describes the reporting system and analysis of 116 off-nominal situation reports from 352 small UAS operations, which were conducted at two flight test ranges in Summer 2019.

Jung, Jaewoo↗

Progress on Modular Unmanned Aircraft Technology

Modular unmanned aerial systems (UAS) are a new development in UAS architecture that holds promise for reusable, reconfigurable hosts for science and autonomy payloads. Modularity of airframe subcomponents lowers costs, facilitates rapid field repair, permits holistic optimization, and enables mass-customization of bespoke platforms customizing the aircraft around a given payload or payloads. Without modular UAS, sensors and instruments often must be designed to fit in a non-modifiable airframe. This talk will present how the nexus of modularity, rapid prototyping and design reuse opens up new tradeoffs, and discuss the envisioned benefits, price paid, and enhanced missions made possible by this new approach to aircraft development.

Dahlgren, Robert P.↗

Stereo Combining NASA Technologies and Partnerships to Transform Current-Day Emergency Response Operations

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an overview of the STEReO project and introduces a stakeholder workshop as a three-day activity to solicit input from the community of emergency response operators and related industry representatives.

Mercer, Joey S.↗

STEReO: Combining NASA Technologies and Partnerships to Transform Current-Day Emergency Response Operations

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA?s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the STEReO project to attendees of the annual North American Aerial Fire Fighting conference (AFFNA 2020).

Mercer, Joey S.↗

Stereo: Combining NASA Technologies and Partnerships to Transform Current-Day Emergency Response Operations

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA's UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the STEReO project to the members of the US Forest Service (USFS) region 5 aerial supervisor steering committee (ASSC).

Mercer, Joey↗

Overview and Initial Results of SAND-E: Semi-Autonomous Navigation for Detrital Environments

Unmanned aerial systems (UAS) and automated terrain analysis for science and navigation are new technologies for planetary exploration. The Mars Helicopter will fly with the Mars2020 rover, the Dragonfly quadcopter will explore Titan, and Soil Properties and Object Classification (SPOC) software will be used for path planning and navigation on the Mars2020 rover. Using an Argo J5 rover instrumented with stereo cameras and Autonomous Soil Assessment System (ASAS) software, and an off the shelf quadcopter, SAND-E tested the use of automated terrain analysis and UAS data for science operations in a Mars-analog environment in Iceland during July of 2019. Scientifically, we sought to determine changes in the physical and chemical properties of sediments along a glacial-fluvial-aeolian transport pathway. Operationally, we tested rover mission-like scenarios that included UAS images and classified terrain images. Here, we present the initial results for both the operations and science elements of the study. Site Selection: A goal of SAND-E is examine sorting and alteration of sediments in fluvial and aeolian environments in both mineral-dominated and glass-dominated basaltic settings. During the first year of the project we focused on a mineral-dominated environment. Selection of the location was based on prior publications that indicated our selected region had a greater abundance of crystalline sediments than other areas fluvial-aeolian settings in Iceland. Other criteria included the presence of both fluvial and aeolian landforms along a transport pathway such that the sediments in transport could be linked to their source rocks. We chose the Skjaldbreidauhraun glacial outwash plain, which sits at the base of Thórisjökull glacier. The site is 30 km north of Thingvellir National Park and ~2 hours from Reykjavik. The outwash plain is fed by two small catchments that drain from the base of the glacier and cut through hyaloclastite and shield volcano bedrock. The drainage progresses from steep alluvial fans near the glacier into a low-sloping fluvial braidplain that becomes confined by the Skjaldbreidur shield volcano and creates a shallow canyon cut into lava bedrock. The fluvial system was a typical braided alluvial environment composed pebble- and cobble-bedded longitudinal bars and sandy channel beds. The river remained active and fluctuated in response to diurnal runoff cycles near the glacier before disappearing into the sandy substrate downstream. The high concentration of suspended sediment in the river was evident by the cloudy water and the silt and clay-sized sediments that draped the channel beds after abandonment and created playas in the lowest sloping areas of the catchment. The entire fluvial system was affected by the winds generated by frontal systems and katabatic flows descending the glacier. This resulted in the formation of aeolian lag deposits and a wind-deflation plain where the fluvial system was not active. Wind ripples and drifts formed in abandoned fluvial channels from aeolian reworking of the sand-sized fluvial sediments. The silt- and clay-sized sediments found in fluvial channels, bar tops, and playas generated dust plumes during high wind events. Our operation sought to capture the variability in this system by sampling from the range of fluvial and aeolian features 6.3 km (proximal), 11.3 km (medial), and 14.4 km (distal) along the river from its origin at the base of glacier.

Ewing, R. C.↗

Introduction to UTM Services & Communication

This presentation provides an overview of NASA's UAS traffic management (UTM) system, defines key concepts, and gives a brief recap of the research done thus far. The UTM system is comprised of four key concepts: UAS Service Suppler (USS), USS Network, UAS Supplemental Data Service Suppliers (SDSP), and the Flight Information Management System (FIMS). Walking through an example UTM operation illustrates the basic contribution of and relationship between each of these components. While this is what a future operation could look like, today we have only started down the road. NASA, and particularly NASA Ames, has spent the last four years on UTM research, of which helped inform both regulation and industry.

Claudatos, Lauren↗

Fit2Fly: A Proof of Concept for Testing the Commercial Feasibility of Unmanned Aerial System Operations

As autonomous Unmanned Aerial Systems (UAS) become more prevalent, improvements in airworthiness assessments, data security, establishing vehicle trust, and more will become necessary to make fleet operations of these systems routine. Currently, these are verified for every UAS vehicle through a time-intensive manual inspection performed by human individuals. This process becomes infeasible when introduced into large-scale operations, so the Fit2Fly project is attempting to address these concerns. Fit2Fly is a multi-year project with a large scope, so we chose to narrow our focus to building a proof-of-concept feasibility simulation in tandem with physical UAS demonstration. This work resulted in a software simulation capable of running asynchronous commercial operations with persistent data modeling in coordination with several autonomous drones using integrated radio and GPS configurations.

Ryan Bonk↗

Display and Automation Considerations for the Airborne Collision Avoidance System Xu

In this paper we examine several display and automation considerations of a collision avoidance system that is currently under development: the Airborne Collision Avoidance System (ACAS) Xu. This study builds on previous work conducted as part of NASA’s Unmanned Aircraft Systems (UAS) Integration into the National Airspace System (NAS) project. ACAS Xu represents the next-generation successor to the Traffic Alert and Collision Avoidance System (TCAS II), wherein the Xu variant is intended for UAS applications. Whereas TCAS II exclusively issues RAs in the vertical dimension, a major distinction between ACAS Xu and previous collision avoidance (CA) systems is the introduction of horizontal and “blended” RAs (i.e., RAs with both horizontal and vertical components). This present work was conducted as an engineering analysis involving two parts. In Part 1, a two-by-two, within-subjects study was performed that manipulated how RAs were presented to a pilot situated at a UAS ground control station. Five participants experienced four experimental trials in which text and aural alerting characteristics were manipulated. In Part 2, another five participants experienced four trials in which the levels of automation were manipulated with regard to the CA and return-to-course (RTC) tasks. The results for Part 1 found no effect of display or alerting configuration on pilot performance. However, it was discovered that pilot response time to RAs greatly depended on the RA type. In particular, pilots were quicker to respond to vertical RAs (M = 4.52 seconds) than horizontal (M = 7.42 seconds) and blended (M = 9.68 seconds) RAs in which both dimensions were issued simultaneously. For Part 2 of the study, pilots found both auto-CA and auto-RTC functions equally useful. Most pilots were comfortable with the automation, however responses were mixed. Three of five participants indicated high levels of comfort with the auto-CA function, while two rated their comfort as low. Pilots’ comfort for the auto-RTC functionality was slightly higher: four out of five pilots gave high ratings, while one pilot gave a low rating. Overall, pilots ordinally ranked their preference for automated functions as auto-CA together with auto-RTC (when an aural alert announces a change between CA and RTC states), auto-CA, and auto-CA and RTC (without the aural state-change announcement). Recommendations for improving the display of automation are also discussed.

collision avoidance↗

Scalable Traffic Management for Emergency Response Operations (STEReO)

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the STEReO project to attendees of the AIAA Aviation conference.

emergency response operations↗

Display and Automation Considerations for the Airborne Collision Avoidance System Xu

In this presentation we examine several display and automation considerations of a collision avoidance system that is currently under development: the Airborne Collision Avoidance System (ACAS) Xu. This study builds on previous work conducted as part of NASA’s Unmanned Aircraft Systems (UAS) Integration into the National Airspace System (NAS) project. ACAS Xu represents the next-generation successor to the Traffic Alert and Collision Avoidance System (TCAS II), wherein the Xu variant is intended for UAS applications. Whereas TCAS II exclusively issues RAs in the vertical dimension, a major distinction between ACAS Xu and previous collision avoidance (CA) systems is the introduction of horizontal and “blended” RAs (i.e., RAs with both horizontal and vertical components). This present work was conducted as an engineering analysis involving two parts. In Part 1, a two-by-two, within-subjects study was performed that manipulated how RAs were presented to a pilot situated at a UAS ground control station. Five participants experienced four experimental trials in which text and aural alerting characteristics were manipulated. In Part 2, another five participants experienced four trials in which the levels of automation were manipulated with regard to the CA and return-to-course (RTC) tasks. The results for Part 1 found no effect of display or alerting configuration on pilot performance. However, it was discovered that pilot response time to RAs greatly depended on the RA type. In particular, pilots were quicker to respond to vertical RAs (M = 4.52 seconds) than horizontal (M = 7.42 seconds) and blended (M = 9.68 seconds) RAs in which both dimensions were issued simultaneously. For Part 2 of the study, pilots found both auto-CA and auto-RTC functions equally useful. Most pilots were comfortable with the automation, however responses were mixed. Three of five participants indicated high levels of comfort with the auto-CA function, while two rated their comfort as low. Pilots’ comfort for the auto-RTC functionality was slightly higher: four out of five pilots gave high ratings, while one pilot gave a low rating. Overall, pilots ordinally ranked their preference for automated functions as auto-CA together with auto-RTC (when an aural alert announces a change between CA and RTC states), auto-CA, and auto-CA and RTC (without the aural state-change announcement). Recommendations for improving the display of automation are also discussed.

collision avoidance↗

A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM)

The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.

In-Time Aviation Safety Management System↗

A Human-in-the-Loop Evaluation of ACAS Xu

As part of the Phase 2 UAS DAA MOPS, a Class 3 DAA system has been under development with the potential to resolve many of the limitations of Class 1 and 2 systems. A Class 3 system would combine the DAA and CA functions into a single, unified system, and would also extend the CA capabilities relative to TCAS II. Class 3 is enabled by the Airborne Collision Avoidance System (ACAS) XU, a next generation CA system developed specifically for UAS operations. Unlike Class 2 systems, ACAS XU provides CA protection against both cooperative and non-cooperative traffic. Class 3 systems also expand the CA logic to allow horizontal RAs in addition to vertical RAs. The purpose of the current study was to evaluate ACAS XU in a real-time, HITL simulation. The latest version of ACAS XU was implemented and pilots were tasked with responding to scripted traffic conflicts over the course of four experimental trials. Variables included the location of the ACAS XU guidance information (standalone vs. integrated) and traffic conflict type (DAA or CA threat). Sixteen active UAS pilots participated in the study, with ATC and ‘pseudo’ pilots acting as airspace confederates. Results showed that pilots were able to maintain DWC with ACAS XU at a rate comparable to previous research (~5%). Compliance rates to initial RAs were high (~90%) but dropped significantly when the target heading value issued during horizontal RAs were updated over the course of an encounter (30-70%). The implications of these findings on the display, alerting, and guidance requirements for Class 3 systems will be discussed.

unmanned aircraft systems↗

Small Unmanned Aircraft System Communications and Navigation Performance

NASA performed research and development of technologies and requirements for traffic management of small Unmanned Aircraft Systems (UAS). In this effort, four measures of performance (MOPs) were developed to understand the performance of small UAS communications and navigation systems in urban operations. This Technical Memorandum (TM) describes UAS Traffic Management (UTM) operational architecture, UTM Technical Capability Level 4 (TCL4) flight tests that took place in two different urban settings, the four MOPs, and the TCL4 MOP results.

Unmanned Aviation Systems Traffic Management↗

A Human-in-the-Loop Evaluation of ACAS Xu

As part of the Phase 2 UAS DAA MOPS, a Class 3 DAA system has been under development with the potential to resolve many of the limitations of Class 1 and 2 systems. A Class 3 system would combine the DAA and CA functions into a single, unified system, and would also extend the CA capabilities relative to TCAS II. Class 3 is enabled by the Airborne Collision Avoidance System (ACAS) XU, a next generation CA system developed specifically for UAS operations. Unlike Class 2 systems, ACAS XU provides CA protection against both cooperative and non-cooperative traffic. Class 3 systems also expand the CA logic to allow horizontal RAs in addition to vertical RAs. The purpose of the current study was to evaluate ACAS XU in a real-time, HITL simulation. The latest version of ACAS XU was implemented and pilots were tasked with responding to scripted traffic conflicts over the course of four experimental trials. Variables included the location of the ACAS XU guidance information (standalone vs. integrated) and traffic conflict type (DAA or CA threat). Sixteen active UAS pilots participated in the study, with ATC and ‘pseudo’ pilots acting as airspace confederates. Results showed that pilots were able to maintain DWC with ACAS XU at a rate comparable to previous research (~5%). Compliance rates to initial RAs were high (~90%) but dropped significantly when the target heading value issued during horizontal RAs were updated over the course of an encounter (30-70%). The implications of these findings on the display, alerting, and guidance requirements for Class 3 systems will be discussed.

unmanned aircraft systems↗

A Human-in-theLoop Evaluation of ACAS Xu

As part of the Phase 2 UAS DAA MOPS, a Class 3 DAA system has been under development with the potential to resolve many of the limitations of Class 1 and 2 systems. A Class 3 system would combine the DAA and CA functions into a single, unified system, and would also extend the CA capabilities relative to TCAS II. Class 3 is enabled by the Airborne Collision Avoidance System (ACAS) XU, a next generation CA system developed specifically for UAS operations. Unlike Class 2 systems, ACAS XU provides CA protection against both cooperative and non-cooperative traffic. Class 3 systems also expand the CA logic to allow horizontal RAs in addition to vertical RAs. The purpose of the current study was to evaluate ACAS XU in a real-time, HITL simulation. The latest version of ACAS XU was implemented and pilots were tasked with responding to scripted traffic conflicts over the course of four experimental trials. Variables included the location of the ACAS XU guidance information (standalone vs. integrated) and traffic conflict type (DAA or CA threat). Sixteen active UAS pilots participated in the study, with ATC and ‘pseudo’ pilots acting as airspace confederates. Results showed that pilots were able to maintain DWC with ACAS XU at a rate comparable to previous research (~5%). Compliance rates to initial RAs were high (~90%) but dropped significantly when the target heading value issued during horizontal RAs were updated over the course of an encounter (30-70%). The implications of these findings on the display, alerting, and guidance requirements for Class 3 systems will be discussed.

unmanned aircraft systems↗