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At least 217 records · Page 12

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↗

SSI-ARC Flight Test 3 Data Review

The "Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS)" Project conducted flight test program, referred to as Flight Test 3, at Armstrong Flight Research Center from June - August 2015. Four flight test days were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as Autoresolver. 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. Resulting flight test data and analysis results will be used to evaluate the DAA system performance (e.g., trajectory prediction accuracy, threat detection) and to add fidelity to simulation models used to inform Minimum Operating Performance Standards (MOPS) for integrating UAS into routine NAS operations.

detect and avoid↗

Modeling and Simulation Plans in Support of Low Cost, Size, Weight, and Power Surveillance Systems for Detecting and Tracking Non-Cooperative Aircraft

RTCA Special Committee (SC) 228 has initiated a second phase for the development of minimum operational performance standards (MOPS) for UAS detect and avoid (DAA) systems. Technologies to enable UAS with less available Size, Weight, and Power (SWaP) will be considered. RTCA SC-228 has established sub-working groups and one of the sub-working groups is focused on aligning modeling and simulations activities across all participating committee members. This briefing will describe NASAs modeling and simulation plans for the development of performance standards for low cost, size, weight, and power (C-SWaP) surveillance systems that detect and track non-cooperative aircraft. The briefing will also describe the simulation platform NASA intends to use to support end-to-end verification and validation for these DAA systems. Lastly, the briefing will highlight the experiment plan for our first simulation study, and provide a high-level description of our future flight test plans. This briefing does not contain any results or data.

surveillance↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Terminal Operations HITL 1B Primary Results

This presentation provides an overview of the primary results from the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project's second Terminal Operations human-in-the-loop simulation. This talk covers the background of this follow-on experiment, which includes an overview of the first Terminal Operations HITL performed by the project. The primary results include a look at the number and durations of detect and avoid (DAA) alerts issued by the two DAA systems under test. It also includes response time metrics and metrics on the ability of the pilot-in-command (PIC) to maintain sufficient separation. Additional interoperability metrics are included to illustrate how pilots interact with the tower controller. Implications and conclusions are covered at the end.

unmanned aircraft systems↗

Multi-UAS HITL: Primary Results & Automation Workshop Summaries

This presentation covers the primary results from a recently completed human-in-the-loop (HITL) simulation conducted as part of the UAS (Unmanned Aircraft System) integration into the NAS (National Airspace System) project. The HITL examined the impact of multiple (simultaneous) UAS control while performing a demanding mission task and managing scripted conflicts. The scripted conflicts were designed to trigger the detect-and-avoid (DAA) system. This was the first time the DAA system as designed as part of the UAS-NAS project has been applied to multi-UAS control. The second part of the presentation briefly summarizes the takeaways from two workshops held on human-automation interaction considerations for UAS integration. NASA co-hosted and participated in both workshops.

unmanned aircraft systems↗

An Evaluation of UAS Pilot Workload and Acceptability Ratings with Four Simulated Radar Declaration Ranges

Currently, minimum operational performance standards (MOPS) are being developed for a broader range of unmanned aircraft system (UAS) platforms, including smaller UAS that will feature onboard sensors that are low in size, weight, and power, otherwise known as low SWaP. The low SWaP sensors used to detect non-cooperative traffic will have limited declaration ranges compared to those designed for medium-to-large UAS. A human-in-the-loop (HITL) study was conducted examining four possible radar declaration ranges (i.e., 1.5 NM, 2 NM, 2.5 NM, and 3 NM) for a potential low SWaP sensor with a detect and avoid (DAA) system encountering various non-cooperative encounters in Oakland Center airspace. Participants had lower workload, particularly workload associated with temporal demand and effort, in scenarios that featured larger declaration ranges. Furthermore, participants reported better ability to remain DAA well clear within the larger declaration range conditions, specifically with the 2.5 NM and 3 NM conditions.

UAS↗

An Evaluation of UAS Pilot Workload and Acceptability Ratings with Four Simulated Radar Declaration Ranges

Currently, minimum operational performance standards (MOPS) are being developed for a broader range of unmanned aircraft system (UAS) platforms, including smaller UAS that will feature onboard sensors that are low in size, weight, and power, otherwise known as low SWaP. The low SWaP sensors used to detect non-cooperative traffic will have limited declaration ranges compared to those designed for medium-to-large UAS. A human-in-the-loop (HITL) study was conducted examining four possible radar declaration ranges (i.e., 1.5 NM, 2 NM, 2.5 NM, and 3 NM) for a potential low SWaP sensor with a detect and avoid (DAA) system encountering various non-cooperative encounters in Oakland Center airspace. Participants had lower workload, particularly workload associated with temporal demand and effort, in scenarios that featured larger declaration ranges. Furthermore, participants reported better ability to remain DAA well clear within the larger declaration range conditions, specifically with the 2.5 NM and 3 NM conditions.

UAS↗

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Overview for RTCA SC-228

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project started in 2021 under NASA’s Air Traffic Management – eXploration (ATM-X) project. ATM-X as a project is conducting research to support the growth of traditional aviation and new entrants. This presentation discusses the background of the PAAV project as well as it’s current areas of focus around uncrewed aircraft system (UAS) operations. The areas include the development of a flight test ecosystem, detect and avoid, traffic pattern integration, aircraft-to-aircraft communications, and contingency management. The aim of these research areas is to help inform the development of performance standards and FAA-approved procedures for integrating UAS into the national airspace system (NAS). The presentation seeks to describe the PAAV research objectives in sufficient detail to allow the committee to provide feedback on the sub-project's approach and main areas of interest.

uncrewed aircraft systems↗

Alert Timing Assessment for Unmanned Aircraft System Terminal Area Operations

A Detect and Avoid (DAA) system is an essential enabler for integrating Unmanned Aircraft Systems (UAS) into the U.S. National Airspace System. A DAA system uses a suite of sensors, trackers and alerting and guidance algorithms to assist a remote pilot in maintaining separation from airborne traffic. The initial minimum performance standards focused on en route operations; in order to facilitate operations in and around the airport environment, this paper presents the derivation of the early alert threshold for UAS terminal operations.

Unmanned Aircraft Systems↗

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↗

A Provably Correct Floating-Point Implementation of Well Clear Avionics Concepts

The NASA DAIDALUS library provides formal definitions for Detect-and-Avoid avionics concepts such as when an aircraft is well-clear with respect to the surrounding air traffic, i.e., it does not operate in such proximity to create a collision hazard. While several properties are proven correct for DAIDALUS assuming ideal real number arithmetic, an actual implementation that uses floating-point numbers may behave unexpectedly because of round-off errors and run-time exceptions. This paper presents an experience report on the application of a formal methods toolchain to extract and verify floating-point C code from a real-valued specification of the well-clear module of DAIDALUS. This toolchain comprises the PVS theorem prover, the PRECiSA floating-point analyzer and code generator, and the Frama-C analysis suite. The generated code is automatically instrumented to detect when the control flow of the floating-point program may diverge from the ideal real number specification, and it is annotated with contracts that state the maximum accumulated round-off error. The absence of overflows is also formally verified for the generated code. In order to apply the toolchain to an industrial case study such as DAIDALUS, a formally verified pre-processing of the input specification is performed, which includes a program slicing and several semantic-preserving simplifications.

Program verification↗

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↗

Final Overview of ACES Simulation for Evaluation SARP Well-Clear Definitions

The UAS in the NAS project is studying the minimum operational performance standards for unmanned aerial systems (UAS's) detect-and-avoid (DAA) system in order to operate in the National Airspace System. The DoD's Science and research Panel (SARP) Well-Clear Workshop is investigating the time and spatial boundary at which an UAS violates well-clear. NASA is supporting this effort through use of its Airspace Concept Evaluation System (ACES) simulation platform. This briefing presents the final results to the SARP, which will be used to judge the three candidate well-clear definitions, and for the selection of the most operationally suitable option.

detect and avoid↗

Camera Image Transformation and Registration for Safe Spacecraft Landing and Hazard Avoidance

Inherent geographical hazards of Martian terrain may impede a safe landing for science exploration spacecraft. Surface visualization software for hazard detection and avoidance may accordingly be applied in vehicles such as the Mars Exploration Rover (MER) to induce an autonomous and intelligent descent upon entering the planetary atmosphere. The focus of this project is to develop an image transformation algorithm for coordinate system matching between consecutive frames of terrain imagery taken throughout descent. The methodology involves integrating computer vision and graphics techniques, including affine transformation and projective geometry of an object, with the intrinsic parameters governing spacecraft dynamic motion and camera calibration.

Jones, Brandon M.↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Terminal Operations HITL 1: Primary Results

This presentation covers the primary results of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project Terminal Operations Foundational Human-in-the-Loop (HITL) simulation. The study tasked 16 pilots (half with manned piloting experience, and the other half with unmanned piloting experience) with maintaining "well clear" from other traffic while performing three different types of approaches into the Santa Rosa airport. A detect and avoid (DAA) system was provided to pilots to assist their ability to manage separation. The DAA system used in this test conformed to the criteria defined by RTCA Special Committee 228 (SC-228) in their Phase 1 Minimum Operational Performance Standards (MOPS) for UAS intending to operate in the NAS. The Phase 1 system was not designed to account for terminal operations, focusing instead on en route operations. To account for this, three different alerting and guidance configurations were presently tested in order to determine their effect on pilots operating the system in the terminal area. Results indicated that pilots with the alerting and guidance condition that provided the least amount of assistance (fewer alert levels and guidance types) experienced slightly increased pilot response times and rates of losses of separation. Additional data is presented on the effects of approach type and descriptive data on pilot maneuver preferences and ATC interoperability.

terminal environmen↗

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 minimum operational performance standards (MOPS) of detect-and-avoid (DAA) systems for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance could be provided during recovery of well clear separation with a non-cooperative VFR aircraft in addition to horizontal maneuver guidance. Although suppressing vertical maneuver guidance in these situations increased the minimum horizontal separation from 500 to 800 feet, the maximum severity of loss of well clear increased in about 35 of the encounters compared to when a vertical maneuver was preferred and allowed. Additionally, analysis of individual cases led to the identification of a class of encounter where vertical rate error had a large effect on horizontal maneuvers due to the difficulty of making the correct left-right turn decision: crossing conflict with intruder changing altitude. These results supported allowing vertical maneuvers when UAS vertical performance exceeds the relative vertical position and velocity accuracy of the DAA tracker given the current velocity of the UAS and the relative vertical position and velocity estimated by the DAA tracker. Looking ahead, these results indicate a need to improve guidance algorithms by utilizing maneuver stability and near mid-air collision risk when determining maneuver guidance to regain well clear separation.

detect and avoid↗

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↗

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↗