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NASA NTRS2016

Simulation and Flight Test Data Collection to Support Phase 1 Detect-and-Avoid MOPS

The UAS Integration into the NAS (UASNAS) project is studying the minimum operational performance standards for unmanned aerial system (UAS) detect-and-avoid (DAA) systems in order to operate in the National Airspace System (NAS). The project is executing a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. Armstrong Flight Research Center is hosting a VIP Day in conjunction with the UAS-NAS Project's Flight Test 4 activity, and the Ames Project Engineer (or designate) will be presenting a briefing. This briefing will review the data collection and analysis activities for Flight Test 4 within the Separation assurance-Sense-and-avoid Interoperability (SSI) team.

data analysis↗

NASA NTRS2015

Characteristics of a Well Clear Definition and Alerting Criteria for Encounters Between UAS and Manned Aircraft in Class E Airspace

Unmanned aircraft systems (UAS) will be required to equip with a detect-and-avoid (DAA) system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. For a DAA system to satisfy the requirement to stay well clear of other airborne traffic, a quantitative definition of well clear needs to be defined and evaluated. This study investigates the implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the National Airspace System (NAS). The first analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The second analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results presented in this study inform the safety case, requirements development, and the operational environment for DAA minimum operational performance standards.

Safety↗

NASA NTRS2015

Appendix A: NAS-Wide Encounter Rate Evaluation Using Historical Radar Data and the Airspace Concept Evaluation System (ACES)

Regulations that establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions. Those requirements will apply to detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the National Airspace System (NAS) and are determined according to their contribution to the overall level of safety required to operate in the airspace. Several key gaps must be addressed in order to link equipment requirements to an airspace level of safety. Foremost among these is the calculation of the relative effectiveness of a particular system to mitigate violations of a separation standard with other aircraft, which is known as the systems risk ratio. The risk ratio is calculated as the probability of mid-air collision with a DAA system divided by the probability of mid-air collision without a DAA system. The risk ratio of a DAA system, in combination with the risk ratios of other collision avoidance mitigations, will determine the overall safety of the airspace measured in terms of the number of mid-air collisions per flight hour. Defining the required risk ratio that the DAA system needs to ensure the safety of the airspace requires an evaluation of the current airspace and a simulated evaluation that incorporates UAS aerodynamic performance and the mission characteristics of future UAS operations that are projected to be conducted in areas that interact with current operations. These evaluations will produce the frequency of encounters that currently exist in the airspace and those that could be generated with the introduction of UAS. Together, the frequency of encounters, an evaluation of unmitigated risk of collision, and a desired level of safety of the airspace will yield a required risk ratio of the DAA system. This study will focus on evaluating the encounter rates between aircraft based on historical radar data and encounter rates that could occur based on simulated UAS missions.

Unmanned Aircraft Systems↗

NASA NTRS2016

Piloted Well Clear Performance Evaluation of Detect and Avoid Systems with Suggestive Guidance

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.

detect and avoid↗

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 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

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 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 NTRS2017

Maintain and Regain Well Clear: Maneuver Guidance Designs for Pilots Performing the Detect-and-Avoid Task

In order to support the future expansion and integration of Unmanned Aircraft Systems (UAS), ongoing research efforts have sought to produce findings that inform the minimum display information elements required for acceptable UAS pilot response times and traffic avoidance. Previous simulations have revealed performance benefits associated with DAA displays containing predictive information and suggestive maneuver guidance tools in the form of banding. The present study investigated the impact of various maneuver guidance display configurations on detect-and-avoid (DAA) task performance in a simulated airspace environment. UAS pilots ability to maintain DAA well clear was compared between displays with either the presence or absence of green DAA bands, which indicated conflict-free flight regions. Additional display comparisons assessed pilots ability to regain DAA well clear with two different guidance presentations designed to aid in DAA well clear recovery during critical encounters. Performance implications and display considerations for future UAS DAA systems are discussed.

unmanned aircraft systems (UAS)↗

NASA NTRS2016

Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling (JADEM) and Its Applications

A brief overview of Java Architecture for Detect-and-Avoid (DAA) Extensibility and Modeling (JADEM) and its applications to UAS (Unmanned Aircraft System) Integration in the NAS (National Airspace System) Project.

UAS↗

NASA NTRS2015

NASA ACES V&V Alignment Briefing

Santiago, Confesor↗

NASA NTRS2014

Assuring Ground-Based Detect and Avoid for UAS Operations

One of the goals of the Marginal Ice Zones Observations and Processes Experiment (MIZOPEX) NASA Earth science mission was to show the operational capabilities of Unmanned Aircraft Systems (UAS) when deployed on challenging missions, in difficult environments. Given the extreme conditions of the Arctic environment where MIZOPEX measurements were required, the mission opted to use a radar to provide a ground-based detect-and-avoid (GBDAA) capability as an alternate means of compliance (AMOC) with the see-and-avoid federal aviation regulation. This paper describes how GBDAA safety assurance was provided by interpreting and applying the guidelines in the national policy for UAS operational approval. In particular, we describe how we formulated the appropriate safety goals, defined the processes and procedures for system safety, identified and assembled the relevant safety verification evidence, and created an operational safety case in compliance with Federal Aviation Administration (FAA) requirements. To the best of our knowledge, the safety case, which was ultimately approved by the FAA, is the first successful example of non-military UAS operations using GBDAA in the U.S. National Airspace System (NAS), and, therefore, the first nonmilitary application of the safety case concept in this context.

Detect-and-Avoid↗

NASA NTRS2015

The Impact of Integrated Maneuver Guidance Information on UAS Pilots Performing the Detect and Avoid Task

The integrated human-in-the-loop (iHITL) simulation examined the effect of four different Detect-and-Avoid (DAA) display concepts on unmanned aircraft system (UAS) pilots' ability to maintain safe separation. The displays varied in the type and amount of guidance they provided to pilots. The study's background and methodology are discussed, followed by the 'measured response' data (i.e., pilots' end-to-end response time in reacting to traffic alerts on their DAA display). Results indicate that display type had a significant impact on how long pilot's spent interacting with the interface (i.e., edit times).

detect and avoid↗

NASA NTRS2014

UAS Integration into the NAS: iHTL: DAA Display Evaluation Preliminary Results

The integrated human-in-the-loop (iHITL) simulation examined the effect of four different Detect-and-Avoid (DAA) display concepts on unmanned aircraft system (UAS) pilots' ability to maintain safe separation. The displays varied in the type and amount of guidance they provided to pilots. The study's background and methodology are discussed, followed by a presentation of the preliminary 'measured response' data (i.e., pilots' end-to-end response time in reacting to traffic alerts on their DAA display). Results indicate that display type had moderate to no affect on pilot measured response times.

unmanned aircraft systems↗

NASA NTRS2016

Flight Test 4 Preliminary Results: NASA Ames SSI

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements as well as the safety substantiation and end-to-end assessment of DAA system performance. The Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS) Project conducted flight test program, referred to as Flight Test 4, at Armstrong Flight Research Center from April -June 2016. Part of the test flights were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as JADEM (Java Architecture for DAA Extensibility and Modeling). The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Flight test 4 has four objectives: (1) validate DAA requirements in stressing cases that drive MOPS requirements, including: high-speed cooperative intruder, low-speed non-cooperative intruder, high vertical closure rate encounter, and Mode CS-only intruder (i.e. without ADS-B), (2) validate TCASDAA alerting and guidance interoperability concept in the presence of realistic sensor, tracking and navigational errors and in multiple-intruder encounters against both cooperative and non-cooperative intruders, (3) validate Well Clear Recovery guidance in the presence of realistic sensor, tracking and navigational errors, and (4) validate DAA alerting and guidance requirements in the presence of realistic sensor, tracking and navigational errors. The results will be presented at RTCA Special Committee 228 in support of final verification and validation of the DAA MOPS.

Detect-And-Avoid (DAA)↗

NASA NTRS2017

Ensuring Interoperability Between Unmanned Aircraft Detect-and-Avoid and Manned Aircraft Collision Avoidance

The Unmanned Aircraft Systems (UAS) community in the United States has identified the need for a collision avoidance region in which UAS Detect-and-Avoid (DAA) vertical guidance is restricted to preclude interoperability issues with manned aircraft collision avoidance system vertical resolution advisories (RAs). This paper documents the process by which the collision avoidance region was defined. Three candidate definitions were evaluated on 1.3 million simulated pairwise encounters between UAS and manned aircraft covering a wide range of horizontal and vertical closure rates, angles, and miss distances. Each definition was evaluated with regard to UAS DAA interoperability with manned aircraft collision avoidance in terms of how well it achieved: 1) the primary objective of restricting DAA vertical guidance prior to RAs when the aircraft are close, and 2) the secondary objective of avoiding unnecessary restrictions of DAA vertical guidance at DAA alerts when the aircraft are further apart. The collision avoidance region definition that fully achieves the primary objective and best achieves the secondary objective was recommended to and accepted by the UAS community in the United States. By this definition, UAS and manned aircraft are in the collision avoidance region where DAA vertical guidance is restricted when the time to closest point of approach (CPA) is less than 50 seconds and either the time to co-altitude is less than 50 seconds or the current vertical separation is less than 800 feet.

unmanned aircraft systems; collision avoidance; in↗

NASA NTRS2016

Unmanned Aircraft Systems Human-in-the-Loop Controller and Pilot Acceptability Study: Collision Avoidance, Self-Separation, and Alerting Times (CASSAT)

The Federal Aviation Administration (FAA) has been mandated by the Congressional funding bill of 2012 to open the National Airspace System (NAS) to Unmanned Aircraft Systems (UAS). With the growing use of unmanned systems, NASA has established a multi-center "UAS Integration in the NAS" Project, in collaboration with the FAA and industry, and is guiding its research efforts to look at and examine crucial safety concerns regarding the integration of UAS into the NAS. Key research efforts are addressing requirements for detect-and-avoid (DAA), self-separation (SS), and collision avoidance (CA) technologies. In one of a series of human-in-the-loop experiments, NASA Langley Research Center set up a study known as Collision Avoidance, Self-Separation, and Alerting Times (CASSAT). The first phase assessed active air traffic controller interactions with DAA systems and the second phase examined reactions to the DAA system and displays by UAS Pilots at a simulated ground control station (GCS). Analyses of the test results from Phase I and Phase II are presented in this paper. Results from the CASSAT study and previous human-in-the-loop experiments will play a crucial role in the FAA's establishment of rules, regulations, and procedures to safely, efficiently, and effectively integrate UAS into the NAS.

Comstock, James R., Jr.↗

NASA NTRS2014

ACES Study of DAA-Mitigated UAS Operations SC-228 Requirements Sub Group

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements as well as the safety substantiation and end-to-end assessment of DAA system performance. A recent study conducted using NASA's ACES (Airspace Concept Evaluation System) simulation capability begins to address questions surrounding the development of draft MOPS for DAA systems by assessing DAA performance in a NAS-wide context. ACES analyses were conducted to determine the impact of varying elements of UAS pilot performance and uncertainty mitigations on DAA system performance. Simulations were conducted with recorded cooperative and non-cooperative VFR (Visual Flight Rules) traffic to accurately model UAS encounters with other NAS traffic (ATC (Air Traffic Control) being responsible for separation with other IFR (Instrument Flight Rules) aircraft) and with roughly 25, 000 simulated UAS operations The number of Loss of Well Clear (LoWC) events were recorded across the range of independent variables: pilot response time, horizontal LoWC prediction buffer and horizontal LoWC resolution buffer. The number of LoWC events was compared to the unmitigated case (without the benefit of a DAA system) to determine the resultant risk-ratio for each of 8 simulation conditions. The parameter trades presented by the resultant DAA system performance (risk ratio) will be used by SC 228 to inform decisions about future requirements development and validation efforts.

Detect-and-Avoid↗