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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 NTRS2021

Detect-and-Avoid Safety and Operational Suitability Analysis using an Electro-Optical/Infared Sensor Model

This report documents a closed-loop analysis of an DAA system using a Electro/Optical sensor model. Safety and operational suitability metrics are computed. Results show that the safety metrics are most sensitive to the angular rate accuracy of the intruder aircraft. Trade-off between safety and operationl suitability metrics is discussed. Results from this work directly inform the requirements of an electro/optical sensors for detect-and-avoid.

Detect-and-avoid↗
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 NTRSDate not supplied

Adaptive Stress Testing of Collision Avoidance Systems for Small UASs with Deep Reinforcement Learning

The next-generation Airborne Collision Avoidance System for smaller UASs (ACAS sXu) is currently being developed and tested by the Federal Aviation Administration (FAA) to provide detect-and-avoid capability for small unmanned aircraft operating beyond line-of-sight. Due to the complexity and safety-critical nature of the system, safety validation is important not only for the certification of the final system, but also for informing changes during the iterative development process. In this paper, we analyze a prototype of ACAS sXu in simulated aircraft encounters to discover scenarios of small near mid-air collisions (sNMACs), an important safety event in which two aircraft come closer than 50 feet horizontally and 15 feet vertically. Due to the size and complexity of the system as well as rarity of sNMAC events, traditional methods such as Monte Carlo testing often require informed setup and targeting to elicit failures. However, such a dependence on domain knowledge can be incompatible with the independent verification and validation (IV&V) process, the aim of which is to discover unforeseen issues. To address these challenges, we apply an accelerated validation method called adaptive stress testing (AST) to find the most likely sNMAC scenarios without reliance on system introspection. AST uses reinforcement learning to adapt the search towards the most promising areas of the search space as it progresses. We use a state-of-the-art deep reinforcement learning algorithm, proximate policy optimization, to more efficiently search the large and continuous state space. We find that this approach significantly improves the performance of AST compared to a prior approach based on Monte Carlo tree search. We perform experiments using AST to find sNMAC events under various encounter configurations, varying parameters pertaining to dynamics and coordination. Our experiments show AST to be very effective at finding sNMAC scenarios. We summarize our findings, presenting high-level categories of discovered sNMACs and specific examples of encounters in each category.

aircraft collision avoidance↗
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 NTRS2021

UAS Integration in the NAS Flight Test 6: Full Mission Results

Recent standards development efforts for the integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) such as those in RTCA Inc. Special Committee 228 (SC-228) have focused on relatively large UAS transitioning to and from Class A airspace. In an effort to expand the range of vehicle classes that can access the NAS, the NASA UAS Integration in the NAS project has investigated Low Size, Weight, and Power (Low SWaP) technologies that would allow smaller UAS to detect-and-avoid (DAA) traffic. Through batch and human in the loop (HITL) simulation studies, the UAS Integration in the NAS DAA subproject have identified candidate performance standards that would contribute to enabling extended Low SWaP, UAS operations under 10,000 feet. These candidate performance standards include minimum field of regard (FOR) values for Low SWaP air surveillance sensors as well as a DAA well-clear (DWC) definition which can be applied to non-cooperative traffic to reduce the required maneuver initiation range. To test the assumptions of the project’s simulation studies and validate the candidate performance standards, a live flight research event was executed at NASA Armstrong Flight Research Center. The UAS Integration in the NAS Project Flight Test 6 Full Mission sought to characterize UAS pilot responses to traffic conflicts using a representative Low SWAP DAA system in an operational NAS environment. To achieve this, live, virtual and constructive distributed environment (LVC-DE) elements were combined to simulate a sector of Oakland center airspace and induce encounters with a live, manned aircraft. A Navmar Applied Sciences Tigershark XP was used as the UAS ownship and was integrated into the test architecture to enable it to be controlled from a Vigilant Spirit Control Station (VSCS) research ground control station. Qualified UAS pilots were recruited to act as subject pilots under test (SPUT) to control the Tigershark XP in a simulated mission while coordinating with a participating air traffic controller in simulated airspace. The intruder speed, intruder equipage and encounter geometry were varied between six scripted encounters per SPUT. Various metrics were collected including pilot reaction time from the onset of DAA alert, ATC coordination rate, probability and severity of losses of DAA well clear, and subjective ratings of system acceptability. The implications of these results on the development of standards for Low SWAP DAA systems will be discussed.

UAV↗
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 NTRS2018

UTM UAS Service Supplier Development: Sprint 2 Toward Technical Capability Level 4

NASA's UAS Traffic Management (UTM) Project has been tasked with developing concepts and initial implementations for integrating and managing small unmanned aircraft systems (UAS) into the low altitude airspace. To accomplish this task, the UTM Project planned a phased approach based on four Technical Capability Levels (TCLs). As of this writing, TCL4 is currently in development for a late Spring 2019 flight demonstration. This TCL is focused on operations in an urban environment and includes the handling of high density environments, large-scale off-nominal conditions, vehicle-to-vehicle communications, detect-and-avoid technologies, communication requirements, public safety operations, airspace restrictions, and other related goals. Through research and testing to date, NASA has developed an architecture for UTM that depends on commercial entities collaboratively providing services that are traditionally provided by the Air Navigation Service Provider (ANSP) in manned aviation. A key component of this architecture is the UAS Service Supplier (USS), which acts as a communications bridge between UAS operators and the ANSP when necessary. In addition, the collection of USSs form a USS Network to collaboratively manage the airspace through the sharing of data and the adherence to a standard or set of standards required to participate in this USS Network. This document provides a record of the second of four planned steps in the development of interoperable USSs that will ultimately support TCL4 flight testing and formalization of the overall UTM concept. To develop these USSs and their underlying specifications, NASA has planned a series of "Sprints" to work with industry partners in implementing the features and develop proposed specifications for USSs in order to to participate in TCL4. This report describes Sprint Two. In this Sprint, there was a major theme with four goals. The theme was the development and testing of a new USS discovery system, to better enable USSs to find and communicate with each other. The goals supporting this theme were: participants needed to implement and exercise the discovery service for USS-USS communications; USSs needed to demonstrate strategic deconfliction through operation sharing; the systems were to use discovery to aid in handling off-nominal operations; and finally, there was an investigation of an initial off-nominal reporting capability.

software engineering↗
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↗
NASA NTRS2022

Effects of Unmanned Aircraft Voice Communication Delay on En Route Air Traffic Management Operations

The present study investigated the effects of remotely piloted unmanned aircraft (UA) voice communication delay on air traffic management operations with different background sector traffic-volume levels. Three one-way UA voice delay lengths of 400, 900, and 2,000 milliseconds (ms) were tested, representing the currently estimated transmission delays for terrestrial, satellite communication (SATCOM), and long SATCOM Command and Control Link System, respectively. All delay values exceeded 390 ms, the FAA’s current requirement for the maximum communication latency in the National Airspace System. Eight retired en route air traffic controllers (ATCs) and eight remote pilots (RPs) participated in a human-in-the-loop simulation study, where a simulated UA flight transitioned through an Oakland en route low-altitude sector to a local non-towered airport. The results showed that, when the 2,000-ms voice delay was present, radio transmission step-ons and detect-and-avoid (DAA) alert level elevations increased. In addition, ATC workload, ATC acceptability for the UA, and RP acceptability for the DAA were negatively affected only when the UA had a 2,000-ms voice delay under the high traffic-volume condition, but not in the other conditions.

remotely piloted unmanned aircraft, voice delay, s↗
NASA NTRSDate not supplied

Effects of Unmanned Aircraft Voice Communication Delay on En Route Air Traffic Management Operations

The present study investigated the effects of remotely piloted unmanned aircraft (UA) voice communication delay on air traffic management operations with different background sector traffic-volume levels. Three one-way UA voice delay lengths of 400, 900, and 2,000 milliseconds (ms) were tested, representing the currently estimated transmission delays for terrestrial, satellite communication (SATCOM), and long SATCOM Command and Control Link System, respectively. All delay values exceeded 390 ms, the FAA’s current requirement for the maximum communication latency in the National Airspace System. Eight retired en route air traffic controllers (ATCs) and eight remote pilots (RPs) participated in a human-inthe-loop simulation study, where a simulated UA flight transitioned through an Oakland en route low-altitude sector to a local non-towered airport. The results showed that, when the 2,000-ms voice delay was present, radio transmission step-ons and detect-and-avoid (DAA) alert level elevations increased. In addition, ATC workload, ATC acceptability for the UA, and RP acceptability for the DAA were negatively affected only when the UA had a 2,000-ms voice delay under the high traffic-volume condition, but not in the other conditions.

remotely piloted unmanned aircraft, voice delay, s↗
NASA NTRS2018

UTM UAS Serivce Supplier Development: Sprint 1 Toward Technical Capability Level 4

NASA's UAS Traffic Management (UTM) Project has been tasked with developing concepts and initial implementations for integrating and managing small unmanned aircraft systems (UAS) into the low altitude airspace. To accomplish this task, the Project planned a phased approach based on four Technical Capability Levels (TCLs). As of this writing, TCL4 is currently in development for a late Spring 2019 flight demonstration. This TCL is focused on operations in an urban environment and includes the handling of high density and large-scale off-nominal conditions, vehicle-to-vehicle communications, detect-and-avoid technologies, communication requirements, public safety operations, airspace restrictions, and other related goals. Through research and testing to date, NASA has developed an architecture for UTM that depends on commercial entities collaboratively providing services that are traditionally provided by the Air Navigation Service Provider(ANSP) in manned aviation. A key component of this architecture is the UAS Service Supplier (USS), which acts as a communications bridge between UAS operators and the ANSP when necessary. In addition, the collection of USSs form a USS Network to collaboratively manage the airspace through the sharing of data and the adherence to a standard or set of standards required to participate in this USS Network. This document provides a record of the first step in the development of interoperable USSs that will ultimately support TCL4 flight testing and formalization of the overall UTM concept. To develop these USSs and the underlying specifications for them, NASA has planned a series of "Sprints" to work with industry partners in implementing the features and proposed specifications for USSs to participate in TCL4. This report describes Sprint One. In this Sprint, the focus was on establishing a baseline for the Application Programming Interfaces (APIs) and their associated data models. In addition, the concept of UAS Volume Reservations (UVR) (areas that impose restrictions on sUAS that are allowed to operate) was tested. NASA provided the specifications and iterated on them with partners while implementers developed to those specifications. NASA then tested each partner's implementation to ensure compatibility with all other implementers. This process helped all stakeholders gain confidence that the foundation for future Sprints was solid.

UAS service supplier↗
NASA NTRS2021

Weather Intelligent Navigation Data and Models for Aviation Planning (WINDMAP)

WINDMAP addresses the emerging needs in the aviation community of providing real-time weather forecasting to improve the safety of low altitude aircraft operations. This is accomplished through the integration of real-time observations from autonomous systems, such as drones and urban air taxis, with numerical weather prediction models and flight management and safety systems. To solve this problem, several technical challenges have been identified. These include (1) developing autonomous UAS capable of conducting observations accurately and reliably; (2) determining the number and frequency of required observations and the sensitivity of these observations in data sparse regions of the lower atmosphere;(3) assimilating dense observational data into models in real-time with sufficient resolution and accuracy; (4) developing novel physics-based reduced order models capable of incorporating diverse data sets; and (5)integrating real-time forecasting into UTM and DAA (detect-and-avoid) architectures for path planning and navigation. The goal of this proposed effort is to demonstrate the value of using small UAS to collect measurements of the dynamic and thermodynamic properties of the lower atmosphere at scales that match or exceed the spatio-temporal resolution of today’s best numerical weather prediction models

Koushik Datta↗
NASA NTRS2015

An Evaluation of Detect and Avoid Displays for UAS: The Effect of Information Level and Display Location on Pilot Performance

The pilot-in-the-loop Detect-and-Avoid (DAA) task requires the pilot to carry out three major functions: 1) detect a potential threat, 2) determine an appropriate resolution maneuver, and 3) execute that resolution maneuver via the GCS control and navigation interface(s). The purpose of the present study was to examine two main questions with respect to DAA display considerations that could impact pilots ability to maintain well clear from other aircraft. First, what is the effect of a minimum (or basic) information display compared to an advanced information display on pilot performance? Second, what is the effect of display location on UAS pilot performance? Two levels of information level (basic, advanced) were compared across two levels of display location (standalone, integrated), for a total of four displays. The results indicate that the advanced displays had faster overall response times compared to the basic displays, however, there were no significant differences between the standalone and integrated displays.

detect and avoid↗
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 NTRS2019

Detect-and-Avoid Alerting Performance for High-Speed UAS and Non-Cooperative Aircraft

This paper presents a set of experiments designed to assess the viability of using a smaller Detect and Avoid (DAA) volume for large Unmanned Aircraft Systems (UAS) when they are trying to remain well clear of non-cooperative visual flight rules (VFR) aircraft, in compliance with Federal regulations. The current DAA volume was defined for both cooperative and non-cooperative VFR traffic by the work of RTCA Special Committee 228 in 2017, in what is referred to in this paper as the Phase 1 standards. Subsequent work by the committee has been focused on enabling operations by smaller UAS that cannot carry the heavy radars required for the Phase 1 DAA Minimum Operational Performance Standards (MOPS). The work discussed in this paper will explore whether a Phase 1 UAS using a Phase 1 radar can use the reduced non-cooperative DAA alerting volume being studied for smaller, slower Phase 2 UAS without significantly degrading system safety. The study uses UAS models and background traffic from previous Phase 1 and Phase 2 research to run an unmitigated simulation that will examine alerting performance using different DAA well clear definitions. The primary metrics are also tied to the alerting performance of the DAA system, and include average alerting times, probabilities of missed and late alerts, and the probability of a near mid-air collision given a loss of "well clear," as defined by the DAA system. Results are expected to help RTCA make the determination whether or not the DAA well clear definition for Phase 1 UAS can be reduced for non-cooperative VFR aircraft.

Cone, Andrew C.↗