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NASA NTRS2016

NAS-Wide Fast-Time Simulation Study for Evaluating Performance of UAS Detect-and-Avoid Alerting and Guidance Systems

This presentation contains the analysis results of NAS-wide fast-time simulations with UAS and VFR traffic for a single day for evaluating the performance of Detect-and-Avoid (DAA) alerting and guidance systems. This purpose of this study was to help refine and validate MOPS alerting and guidance requirements. In this study, we generated plots of all performance metrics that are specified by RTCA SC-228 Minimum Operational Performance Standards (MOPS): 1) to evaluate the sensitivity of alerting parameters on the performance metrics of each DAA alert type: Preventive, Corrective, and Warning alerts and 2) to evaluate the effect of sensor uncertainty on DAA alerting and guidance performance.

DAA Alerting Performance↗

NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗

NASA NTRS2021

Detect-and-Avoid Surveillance Range Requirements for Electro-Optical/Infra-Red Sensors

A detect-and-avoid (DAA) system provides surveillance, alerting, and maneuver guidance (referred to as guidance in this report) that are critical to an unmanned aircraft system’s (UAS) ability to maintain separation from manned aircraft and other unmanned aircraft. The last decade has seen significant progress in the development of DAA requirements, spearheaded by RTCA Special Committee 228 (SC228) and subsequently by other standards organizations such as EUROCAE and ASTM. SC-228’s development of DAA requirements assumes the UAS follows instrument flight rules (IFR) and has a remote pilot or operator in the loop. As of the publication of this document, the SC-228’s latest Minimum Operational Performance Standards (MOPS) for DAA, versioned as DO-365B [1], DAA systems use onboard and/or ground surveillance systems to detect traffic. The surveillance systems must detect both cooperative and non-cooperative air traffic. Cooperative traffic are vehicles that have a broadcasting transponder, while non-cooperative traffic do not, and so must be detected via radar or other sensors. A DAA system’s alerting and guidance functions alert the pilot/operator in the loop of potential hazards, such as intruder aircraft, and provide maneuver solutions which help the pilot/operator avoid or mitigate observed hazards. A UAS pilot is expected to coordinate with air traffic control (ATC) before executing a conflict avoidance maneuver if the type of alert is not urgent enough to require an immediate maneuver.

uncrewed aviation systems↗

NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Detect-And-Avoid (DAA) Systems

The paper describes the Generic Resolution Advisor and Conflict Evaluator (GRACE), a novel alerting and guidance algorithm that combines flexibility, robustness, and computational efficiency. GRACE is "generic" in that it makes no assumptions regarding temporal or spatial scales, aircraft performance, or its sensor and communication systems. Accordingly, GRACE is well suited to research applications where alerting and guidance is a central feature and requirements are fluid involving a wide range of aviation technologies. GRACE has been used at NASA in a number of real-time and fast-time experiments supporting evolving requirements of DAA research, including parametric studies, NAS-wide simulations, human-in-the-loop experiments, and live flight tests.

Unmanned Aircraft↗

NASA NTRS2016

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

This study evaluated the performance of four prototype unmanned aircraft detect-and-avoid (DAA) display configurations, each with different informational elements driven by alerting and guidance algorithms. Sixteen unmanned aircraft pilots flew each combination of the display configurations, with half being given zero DAA surveillance sensor uncertainty and the other half experiencing errors that were comparable, and in some cases slightly better than, errors that were measured in DAA system flight tests. The displays that showed intruder alert information in altitude and heading bands had significantly fewer losses of well clear compared with alternative displays that lacked that information. This difference was significant from a statistical and practical perspective: those losses that did occur lasted for shorter periods and did not penetrate as far into the geometric "separation cylinder" as those in the non-banded displays. A modest level of DAA surveillance sensor uncertainty did not affect the proportion of losses of well clear or their severity. It is recommended that DAA traffic displays implement a band-type display in order to improve the safety of UAS operations in the National Airspace System. Finally, this report provides pilot response time distributions for responding to DAA alerts.

unmanned aircraft system↗

NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Unmanned Aircraft Detect-And-Avoid Systems

The paper describes the Generic Resolution Advisor and Conflict Evaluator (GRACE), a novel alerting and guidance algorithm that combines flexibility, robustness, and computational efficiency. GRACE is generic since it was designed without any assumptions regarding temporal or spatial scales, aircraft performance, or its sensor and communication systems. Therefore, GRACE was adopted as a core component of the Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling, developed by NASA as a research and modeling tool for Unmanned Aerial Systems Integration in the National Airspace System (NAS). GRACE has been used in a number of real-time and fast-time experiments supporting evolving requirements of DAA research, including parametric studies, NAS-wide simulations, human-in-the-loop experiments, and live flight tests.

Unmanned Aircraft↗

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 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 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

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

Ensuring Interoperability between UAS Detect-and-Avoid and Manned Aircraft Collision Avoidance

The 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. They were evaluated with regard to UAS DAA interoperability with manned aircraft collision avoidance systems in terms of: 1) the primary objective of restricting DAA vertical guidance before RAs when the aircraft are close, and 2) the secondary objective of avoiding unnecessary restrictions of DAA vertical guidance at a DAA alert 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--during which DAA vertical guidance is restricted--when the time to closest point of approach 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.

collision avoidance↗

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 NTRS2018

Comparative Analysis of ACAS-Xu and DAIDALUS Detect-and-Avoid Systems

The Detect and Avoid (DAA) capability of a recent version (Run 3) of the Airborne Collision Avoidance System-Xu (ACAS-Xu) is measured against that of the Detect and AvoID Alerting Logic for Unmanned Systems (DAIDALUS), a reference algorithm for the Phase 1 Minimum Operational Performance Standards (MOPS) for DAA. This comparative analysis of the two systems' alerting and horizontal guidance outcomes is conducted through the lens of the Detect and Avoid mission using flight data of scripted encounters from a recent flight test. Results indicate comparable timelines and outcomes between ACAS-Xu's Remain Well Clear alert and guidance and DAIDALUS's corrective alert and guidance, although ACAS-Xu's guidance appears to be more conservative. ACAS-Xu's Collision Avoidance alert and guidance occurs later than DAIDALUS's warning alert and guidance, and overlaps with DAIDALUS's timeline of maneuver to remain Well Clear. Interesting discrepancies between ACAS-Xu's directive guidance and DAIDALUS's "Regain Well Clear" guidance occur in some scenarios.

Davies, Jason T.↗

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 NTRS2020

Detect-and-Avoid: Flight Test 6 Scripted Encounters Data Analysis

The Unmanned Aircraft System (UAS) in the National Airspace System (NAS) project conducted Flight Test 6 (FT6) in 2019. The ultimate goal of this flight test was to produce data to inform RTCA SC-228's Phase II Minimum Operational Performance Standards (MOPS) for Detect and Avoid (DAA) and Low Size, Weight, and Power Sensors. This report documents the analysis of scripted encounters' data. Scripted encounters own were analyzed and categorized based on the outcome of alert, maneuver guidance, and effectiveness of pilots' maneuver in resolving conflicts. Results indicate that UAS pilots' decisions as well as intruder maneuvers are leading factors that contribute to ineffective DAA maneuvers. Results also show that adding buffers to the DAA's suggested minimum turn angle improves effectiveness of the DAA maneuvers.

Wang, Wei-Ching↗