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NASA NTRS2016

UAS Pilot Evaluations of Suggestive Guidance on Detect-and-Avoid Displays

Minimum display requirements for Detect-and-Avoid (DAA) systems are being developed in order to support the expansion of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). The present study examines UAS pilots' subjective assessments of four DAA display configurations with varying forms of maneuver guidance. For each configuration, pilots rated the intuitiveness of the display and how well it supported their ability to perform the DAA task. Responses revealed a clear preference for the DAA displays that presented suggestive maneuver guidance in the form of "banding" compared to an Information Only display, which lacked any maneuver guidance. Implications on DAA display requirements, as well as the relation between the subjective evaluations and the objective performance data from previous studies are discussed.

unmanned aircraft systems↗
NASA NTRS2016

UAS Pilot Evaluations of Suggestive Guidance on Detect-and-Avoid Displays

Minimum display requirements for Detect-and-Avoid (DAA) systems are being developed in order to support the expansion of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). The present study examines UAS pilots subjective assessments of four DAA display configurations with varying forms of maneuver guidance. For each configuration, pilots rated the intuitiveness of the display and how well it supported their ability to perform the DAA task. Responses revealed a clear preference for the DAA displays that presented suggestive maneuver guidance in the form of banding compared to an Information Only display, which lacked any maneuver guidance. Implications on DAA display requirements, as well as the relation between the subjective evaluations and the objective performance data from previous studies are discussed.

unmanned aircraft systems↗
NASA NTRS2017

DANTi: Detect and Avoid iN The Cockpit

Mid-air collision risk continues to be a concern for manned aircraft operations, especially near busy non-towered airports. The use of Detect and Avoid (DAA) technologies and draft standards developed for unmanned aircraft systems (UAS), either alone or in combination with other collision avoidance technologies, may be useful in mitigating this collision risk for manned aircraft. This paper describes a NASA research effort known as DANTi (DAA iN The Cockpit), including the initial development of the concept of use, a software prototype, and results from initial flight tests conducted with this prototype. The prototype used a single Automatic Dependent Surveillance - Broadcast (ADS-B) traffic sensor and the own aircraft's position, track, heading and air data information, along with NASA-developed DAA software to display traffic alerts and maneuver guidance to manned aircraft pilots on a portable tablet device. Initial flight tests with the prototype showed a successful DANTi proof-of-concept, but also demonstrated that the traffic separation parameter set specified in the RTCA SC-228 Phase I DAA MOPS may generate excessive false alerts during traffic pattern operations. Several parameter sets with smaller separation values were also tested in flight, one of which yielded more timely alerts for the maneuvers tested. Results from this study may further inform future DANTi efforts as well as Phase II DAA MOPS development.

Chamberlain, James↗
NASA NTRS2014

Pilot Evaluation of a UAS Detect-and-Avoid System's Effectiveness in Remaining Well Clear

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. Regulators will establish minimum operating standards for DAA effectiveness, but different combinations of algorithms, displays and procedures could be used to meet those standards. The research presented in this paper indicates the effectiveness of the combined pilot-DAA system as a function of the DAA design requirements and provides data that may be used to model the behavior of pilots when employing such systems. Two simulations involving 21 professional unmanned aircraft system (UAS) pilots evaluated eight different DAA system designs in order to assess their ability to maintain the "well clear" separation standard, i.e., the state of maintaining a safe distance from other aircraft that would not normally cause the initiation of a collision avoidance maneuver by either aircraft. When the traffic display was integrated with the primary mission map directly in front of the pilot, there were fewer losses of well clear. Greater warning time provided to the pilot was strongly correlated with success in remaining well clear. Pilots' ability to separate from aircraft with cooperative and non-cooperative surveillance systems was nearly the same after accounting for the amount of alert time provided in each encounter, although the limited surveillance volume for the airborne-equipped aircraft meant alerts tended to occur later and therefore were more difficult to resolve.

detect-and-avoid↗
NASA NTRS2015

Pilot Evaluation of a UAS Detect-and-Avoid System's Effectiveness in Remaining Well Clear

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that allows them to comply with the requirement to see and avoid other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. Although the effectiveness of the DAA system will be set to a minimum threshold by regulators, different combinations of algorithms, displays and procedures could be used to meet that minimum. The research presented in this paper indicates the effectiveness of the combined pilot-DAA system as a function of the DAA design requirements and provides data that may be used to model the behavior of pilots when employing such systems. Over the course of two simulations 21 professional UAS pilots evaluated eight different DAA system designs and metrics were collected on their ability to maintain the well clear separation standard. The independent variables were the time horizon at which pilots were alerted to potential losses of well clear, the location of the traffic display, and the tools and informational elements available on the display to aid the pilot in detecting and resolving those potential losses. In the second experiment the UAS encountered two categories of aircraft: those equipped with simulated transponders that could be seen dozens of miles away and those without that were only detectable by a simulated radar within a range of six nautical miles. The data indicate that integrating the traffic display with the primary mission map directly in front of the pilot reduced the frequency of losses of well clear. Improved detection and resolution tools, including explicit maneuver guidance and a trial planning capability, had less of an effect in reducing the frequency of losses but significantly reduced the time in loss when they occurred. The amount of warning time provided to the pilot had a strong effect on their ability to remain well clear: when alerts were first presented with less than about 15 seconds to a predicted loss of well clear pilots were able to maneuver successfully in only 26 percent of encounters, whereas they were about 83 percent successful when they had more than 15 seconds. Pilots' ability to separate from the two categories of aircraft was nearly the same after accounting for the amount of alert time provided in each encounter, although the limited surveillance volume for the non-transponder equipped aircraft meant alerts tended to occur later and therefore were more difficult to resolve.

loss of well clear↗
NASA NTRSDate not supplied

Terminal Area Size and Switching Technique Analysis for Unmanned Aircraft Systems Operations

Unmanned Aircraft Systems (UAS) need to be able to comply with the Code of Federal Regulations Part 91 ‘see and avoid’ requirement. Detect and avoid (DAA) is an essential enabler for integrating UAS into the National Airspace System. A DAA system is a suite of sensors, trackers, and alerting and guidance algorithms that assists a remote pilot in maintaining separation from airborne traffic. Previous works have focused on operations transiting to and from Class A or special use airspace. More recent efforts have defined DAA system requirements for operations in and around the airport terminal environment. In continuation of this effort, this paper defines the DAA Terminal Area (DTA) size and switching technique for the DAA Well Clear (DWC) volume while transitioning between en route and the terminal area.

Unmanned Aircraft Systems↗
NASA NTRSDate not supplied

Advanced Air Mobility Operations & Automation Part II Technical Lecture

The Airborne Collision Avoidance System X (ACAS X) is a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant – referred to as ACAS XR – is designed to accommodate existing helicopter platforms as well as in-development, electric vertical takeoff and landing concepts, which are critical to the emerging concept of operations referred to as Advanced Air Mobility. The fundamental role of ACAS XR is to provide Detect and Avoid (DAA) and/or Collision Avoidance (CA) protection against airborne traffic. DAA alerting and guidance in the context of ACAS XR is caution-level and “suggestive,” and is to be used by the pilot if, and when, they decide to maneuver against an identified threat to DAA “well clear.” The CA alerting, by contrast, is warning-level and “directive,” with the pilot required to comply with the associated guidance to prevent a predicted Near Midair Collision (NMAC). The CA alerts generated by ACAS XR are referred to as Resolution Advisories (RAs) consistent with previous CA systems. Unlike earlier CA systems, ACAS XR issues RAs in the horizontal and vertical dimensions as well as multi-axis RAs (referred to as “Blended” RAs). According to the Minimal Operational Performance Standards of DAA systems for Unmanned Aircraft Systems, maneuvers to comply with RAs may be automated, whereas maneuvers based on DAA alerting assume a manual response. The current presentation discusses two human-in-the-loop simulations that presented rotorcraft pilots with ACAS XR alerts and guidance in eVTOL simulators with varying levels of automation. It also presents overviews of these studies as well as how they assisted live flight tests, which will occur throughout 2023.

air taxis↗
NASA NTRS2016

UAS-NAS Project Demo - Mini HITL Week 2 Stats

The UAS-NAS Project demo will showcase recent research efforts to ensure the interoperability between proposed UAS detect and avoid (DAA) human machine interface requirements (developed within RTCA SC-228) and existing collision avoidance displays. Attendees will be able to view the current state of the art of the DAA pilot traffic, alerting and guidance displays integrated with Traffic advisory and Collision Avoidance (TCAS) II in the UAS-NAS Project's research UAS ground control station (developed in partnership with the Air Force Research Laboratory). In addition, attendees will have the opportunity to interact with the research UAS ground control station and "fly" encounters, using the DAA and TCAS II displays to avoid simulated aircraft. The display of the advisories will be hosted on a laptop with an external 30" monitor, running the Vigilant Spirit system. DAA advisories will be generated by the JADEM software tool, connected to the system via the LVC Gateway. A repeater of the primary flight display will be shown on a 55" monitor mounted on a stand at the back of the booth to show the pilot interaction to the passersby.

UAS↗
NASA NTRS2016

UAS in the NAS Flight Test Series 4 Overview

Flight Test Series 4 (FT4) provides the researchers with an opportunity to expand on the data collected during the first flight tests. Following Flight Test Series 3, additional scripted encounters with different aircraft performance and sensors will be conducted. FT4 is presently planned for Spring of 2016 to ensure collection of data to support the validation of the final RTCA Phase 1 DAA (Detect and Avoid) Minimum Operational Performance Standards (MOPS). There are three research objectives associated with this goal: Evaluate the performance of the DAA system against cooperative and non-cooperative aircraft encounters Evaluate UAS (Unmanned Aircraft Systems) pilot performance in response to DAA maneuver guidance and alerting with live intruder encounters Evaluate TCAS/DAA (Traffic Alert and Collision Avoidance System/Detect and Avoid) interoperability. This flight test series will focus on only the Scripted Encounters configuration, supporting the collection of data to validate the interoperability of DAA and collision avoidance algorithms.

flight test↗
NASA NTRSDate not supplied

Detect-and-Avoid Maneuver Planning: Benefits of Including Route Recapture

Development of Detect-and-avoid (DAA) systems’ maneuver guidance requirements at RTCA has centered on tactical maneuvers away from the intruder. Recapturing the flight-plan route the initial maneuver is not directly taken into account by most DAA maneuver guidance algorithms. This work demonstrates potential challenges and inefficiencies that can arise in recapturing the route after resolving a conflict. Horizontal resolution trajectories for a test matrix of encounters with varying aircraft speeds and geometries are computed by minimizing either flight time or deviation to serve as a baseline. Turn directions computed from a reference DAA algorithm coupled with a pilot selection model and a second algorithm called Autoresolver (AR) are compared to these baseline resolution trajectories. Baseline results show that turning into the intruder yields favorable cost for most encounters. Additional analysis of pilot response data shows that only three-fourths of pilots’ horizontal maneuvers turn into intruders, a percentage much lower than the baseline results. Improvement to a DAA guidance algorithm based on findings in this work is discussed.

Route Recapture↗
NASA NTRSDate not supplied

Detect-and-Avoid Maneuver Planning: Benefits of Including Route Recapture

Development of Detect-and-avoid (DAA) systems’ maneuver guidance requirements at RTCA has centered on tactical maneuvers away from the intruder. Recapturing the flight-plan route the initial maneuver is not directly taken into account by most DAA maneuver guidance algorithms. This work demonstrates potential challenges and inefficiencies that can arise in recapturing the route after resolving a conflict. Horizontal resolution trajectories for a test matrix of encounters with varying aircraft speeds and geometries are computed by minimizing either flight time or deviation to serve as a baseline. Turn directions computed from a reference DAA algorithm coupled with a pilot selection model and a second algorithm called Autoresolver (AR) are compared to these baseline resolution trajectories. Baseline results show that turning into the intruder yields favorable cost for most encounters. Additional analysis of pilot response data shows that only three-fourths of pilots’ horizontal maneuvers turn into intruders, a percentage much lower than the baseline results. Improvement to a DAA guidance algorithm based on findings in this work is discussed.

Route Recapture↗
NASA NTRS1983

An overview of the demonstration advanced avionics system guest pilot evaluation conducted at Ames Research Center

The guest pilot flight evaluation of the Demonstration Advanced Avionics System (DAAS) is discussed. The results are based on the fifty-nine questionnaires that were completed by the participants. The primary purpose of the pilot evaluation was to expose the Demonstration Advanced Avionics System to the various segments of the general aviation community and solicit comments in order to determine the effectiveness of integrated avionics for general aviation. Segments of the community that were represented in the evaluation are listed. A total of sixty-four (64) flights were conducted in which one hundred and seventeen (117) pilots and observers participated. It was felt that the exposure each subject had with the DAAS was too short to adequately assess the training requirements, pilot workload, and the reconfiguration concept of the DAAS. It is recommended that an operational evaluation of the DAAS be made to assess: the training requirements or varying experience levels, the pilot workload in the ATC environment with unplanned route changes, and the viability of the reconfiguration concept for failures.

Callas, G. P.↗
NASA NTRS2015

Java Architecture for Detect and Avoid Extensibility and Modeling

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. This paper describes a capability called Java Architecture for Detect and Avoid Extensibility and Modeling (JADEM), developed to prototype and help evaluate various DAA technological requirements by providing a flexible and extensible software platform that models all major detect-and-avoid functions. Figure 1 illustrates JADEM's architecture. The surveillance module can be actual equipment on the unmanned aircraft or simulators that model the process by which sensors on-board detect other aircraft and provide track data to the traffic display. The track evaluation function evaluates each detected aircraft and decides whether to provide an alert to the pilot and its severity. Guidance is a combination of intruder track information, alerting, and avoidance/advisory algorithms behind the tools shown on the traffic display to aid the pilot in determining a maneuver to avoid a loss of well clear. All these functions are designed with a common interface and configurable implementation, which is critical in exploring DAA requirements. To date, JADEM has been utilized in three computer simulations of the National Airspace System, three pilot-in-the-loop experiments using a total of 37 professional UAS pilots, and two flight tests using NASA's Predator-B unmanned aircraft, named Ikhana. The data collected has directly informed the quantitative separation standard for "well clear", safety case, requirements development, and the operational environment for the DAA minimum operational performance standards. This work was performed by the Separation Assurance/Sense and Avoid Interoperability team under NASA's UAS Integration in the NAS project.

unmanned aircraft systems↗
NASA NTRS2016

UAS Integration in the NAS Project: Flight Test 3 Data Analysis of JADEM-Autoresolver Detect and Avoid System

The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS Integration in the NAS, aims to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The UAS Integration in the NAS Project conducted a flight test activity, referred to as Flight Test 3 (FT3), involving several Detect-and-Avoid (DAA) research prototype systems between June 15, 2015 and August 12, 2015 at the Armstrong Flight Research Center (AFRC). This report documents the flight testing and analysis results for the NASA Ames-developed JADEM-Autoresolver DAA system, referred to as 'Autoresolver' herein. Four flight test days (June 17, 18, 22, and July 22) were dedicated to Autoresolver testing. The objectives of this test were as follows: 1. Validate CPA prediction accuracy and detect-and-avoid (DAA, formerly known as self-separation) alerting logic in realistic flight conditions. 2. Validate DAA trajectory model including maneuvers. 3. Evaluate TCAS/DAA interoperability. 4. Inform final Minimum Operating Performance Standards (MOPS). Flight test scenarios were designed to collect data to directly address the objectives 1-3. Objective 4, inform final MOPS, was a general objective applicable to the UAS in the NAS project as a whole, of which flight test is a subset. This report presents analysis results completed in support of the UAS in the NAS project FT3 data review conducted on October 20, 2015. Due to time constraints and, to a lesser extent, TCAS data collection issues, objective 3 was not evaluated in this analysis.

flight test↗
NASA NTRS2016

DAIDALUS Observations From UAS Integration in the NAS Project Flight Test 4

In order to validate the Unmanned Aerial System (UAS) Detect-and-Avoid (DAA) solution proposed by standards body RTCA Inc., the National Aeronautics and Space Administration (NASA) UAS Integration in the NAS project, alongside industry members General Atomics and Honeywell, conducted the fourth flight test in a series at Armstrong Flight Research Center in Edwards, California. Flight Test 4 (FT4) investigated problems of interoperability with the TCAS collision avoidance system with a DAA system as well as problems associated with sensor uncertainty. A series of scripted flight encounters between the NASA Ikhana UAS and various "intruder" aircraft were flown while alerting and guidance from the DAA algorithm were recorded to investigate the timeliness of the alerts and correctness of the guidance triggered by the DAA system. The results found that alerts were triggered in a timely manner in most instances. Cases where the alerting and guidance was incorrect were investigated further.

Vincent, Michael J.↗
NASA NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered-in addition to sensor errors for vertical position and vertical rate-when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder's estimated vertical position and vertical rate, as well as the vertical rate error of the UAS' sensor.

UAS in the NAS↗
NASA NTRS2018

Warning Alert HITL Experiment Results

Minimum Operational Performance Standards (MOPS) are being developed to support the integration of Unmanned Aircraft Systems (UAS) in the National Airspace (NAS). Input from subject matter experts and multiple research studies have informed display requirements for Detect-and-Avoid (DAA) systems aimed at supporting timely and appropriate pilot responses to collision hazards. Phase 1 DAA MOPS alerting is designed to inform pilots if an avoidance maneuver is necessary; the two highest alert levels - caution and warning - indicate how soon pilot action is required and whether there is adequate time to coordinate with the air traffic controller (ATC). Additional empirical support is needed to clarify the extent to which warning-level alerting impacts DAA task performance. The present study explores the differential effects of the auditory and visual cues provided by the DAA Warning alert, and performance implications compared to caution-only alerting are discussed.

alerting↗
NASA NTRS2019

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project

Phase 1 of the UAS-NAS (Unmanned Aircraft Systems-National Airspace System) project focused on MOPS (Minimum Operational Performance Standards) development for large UAS transitioning through Class D, E, and G airspace. Phase 2 activities are currently focused on extended UAS operations in Class D, E, and G airspace, as well as sensors and architectures that will enable DAA (Detect and Avoid) equipment to be installed on a wider range of UAS. Encounters with non-cooperative intruders in low altitude airspace under 10,000 feet will be explored for UAS with a low Size, Weight, and Power (SWaP) radar. New sensors for detecting non-cooperative intruder aircraft will have a more limited detection range and field of regard; therefore, the analysis of non-cooperative encounter geometries may help in developing the requirements for an onboard low SWaP radar (and electro-optical sensor). The current simulation, led by HSI (Human Systems Integration Division at NASA Ames Research Center) as part of the DAA subproject, will support efforts toward developing a modified DAA Well Clear (DWC) definition that would be more appropriate for UAS equipped with limited surveillance and aircraft performance capabilities compared to the Phase 1 DAA system. The findings will inform Phase 2 display requirements for alternative surveillance use cases.

Collision Avoidance↗