Engineering topics

Isaacson, Douglas R.

Publications and source records attributed to Isaacson, Douglas R..

15 records

NASA NTRS2019

Airspace Technology Demonstration 3 (ATD-3): Dynamic Routes for Arrivals in Weather (DRAW) Technology Transfer Document Summary Version 2.0

Airspace Technology Demonstration – 3 (ATD-3) is part of NASA’s Airspace Operations and Safety Program (AOSP) – specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the third Research Transition Product (RTP) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan, which is Dynamic Routes for Arrivals in Weather (DRAW). This technology transfer consists of artifacts for DRAW Arrival Metering (AM) Operations delivered in June 2018, DRAW AM updates, and DRAW Extended Metering (XM) Operations. Blue highlighting indicates the new or modified deliverables. Some of the artifacts in this technology transfer have distribution restrictions that need to be followed. Distribution information is noted in each section. DRAW is a trajectory-based system that combines the legacy Dynamic Weather Routes (DWR) weather avoidance technology with an arrival-specific rerouting algorithm and arrival scheduler to improve traffic flows on weather-impacted arrival routes into major airports. First, DRAW identifies flights that could be rerouted to more efficient Standard Terminal Arrival Routes (STARs) that may have previously been impacted by weather. Second, when weather is impacting the arrival routing, DRAW proposes simple arrival route corrections that enable aircraft to stay on their flight plan while avoiding weather. The DRAW system proposes reroutes early enough to allow Time Based Flow Management (TBFM) to make the necessary schedule adjustments. As a result, metering operations can be sustained longer and more consistently in the presence of weather because the arrival schedule accounts for the dynamic routing intent of arrival flights to deviate around weather. The first DRAW tech transfer in June 2018 focused on arrival metering operations with the DRAW algorithm implemented in the NASA Center TRACON Automation System (CTAS) automation software. This tech transfer delivery includes updates for DRAW implemented in FAA’s TBFM 4.7 automation software and preliminary research into DRAW for XM operations.

Isaacson, Douglas R.↗

NASA NTRS2019

Dynamic Routes for Arrivals in Weather: Concept Overview and Status

Concept overview and status for the ATD-3 (Air Traffic Management Technology Demonstration-3) Dynamic Routes for Arrivals in Weather (ATD-3 DRAW) project.

Isaacson, Douglas R.↗

NASA NTRS2018

Laboratory Evaluation of Dynamic Routing of Air Traffic in an En Route Arrival Metering Environment

Arrival air traffic operations in the presence of convective weather are subject to uncertainty in aircraft routing and subsequently in flight trajectory predictability. Current management of arrival operations in weather-impacted airspace results in significant flight delay and suspension of arrival metering operations. The Dynamic Routing for Arrivals in Weather (DRAW) concept provides flight route amendment advisories to Traffic Management Coordinators to mitigate the impacts of convective weather on arrival operations. DRAW provides both weather conflict and schedule information for proposed route amendments, allowing air traffic managers to simultaneously evaluate weather avoidance routing and potential schedule and delay impacts. Subject matter experts consisting of retired Traffic Management Coordinators and retired Sector Controllers with arrival metering experience participated in a simulation study of Fort Worth Air Route Traffic Control Center arrival operations. Data were collected for Traffic Management Coordinator and Sector Controller participants over three weeks of simulation activities in October, 2017. Traffic Management Coordinators reported acceptable workload levels, a positive impact on their ability to manage arrival traffic while using DRAW, and initiated weather mitigation reroutes earlier while using DRAW. Sector Controllers also reported acceptable workload levels while using DRAW.

Air Traffic Management↗

NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3): Dynamic Routes for Arrivals in Weather (DRAW) Technology Transfer Document Summary Version 1.0

DRAW↗

NASA NTRS2016

FT4 Data Analysis Summary (SSI-ARC)

Standards for Unmanned Aircraft System (UAS) Detect-and-Avoid (DAA) systems are currently being developed under the auspices of the RTCA Special Committee 228 (SC-228). To support the development of these standards, a series of flight tests has been conducted at NASAs Armstrong Flight Research Center (NASA-AFRC). The fourth in this series of flight test activities (Flight Test 4, or simply FT4) was conducted during the Spring and Summer of 2016. FT4 supported the objectives of numerous organizations working toward UAS DAA Minimum Operational Performance Standards (MOPS) and UAS DAA Radar MOPS. The summary provided herein is limited to the objectives, analysis and conclusions of the NASA Ames Research Center (NASA-ARC) SSI team toward the refinement of UAS DAA MOPS. This document provides a high-level overview of FT4 and the SSI-ARC objectives, a summary of the data analysis methodology and recommendations for UAS DAA MOPS refinements based on the data analysis results. A total of 72 encounters were flown to support SSI-ARC objectives. Test results were generally consistent with acceptable UAS DAA system performance and will be considered in broader SC-228 requirements validation efforts. Observed alert lead times indicated acceptable UAS DAA alerting performance. Effective interoperability between the UAS DAA system and the Traffic Alert and Collision Avoidance System (TCAS) was observed with one notable exception: TCAS Resolutions Advisories (RA) were observed in the absence of any DAA alert on two occasions, indicating the need for alert parameter refinement. Findings further indicated the need for continued work in the areas of DAA Well Clear Recovery logic and alert stability for Mode-C-only intruders. Finally, results demonstrated a high level of compliance with a set of evaluation criteria designed to provide anecdotal evidence of acceptable UAS DAA system performance.

UAS Test Flight↗

NASA NTRS2016

Air Traffic Controller Acceptability of Unmanned Aircraft System Detect-and-Avoid Thresholds

A human-in-the-loop experiment was conducted with 15 retired air traffic controllers to investigate two research questions: (a) what procedures are appropriate for the use of unmanned aircraft system (UAS) detect-and-avoid systems, and (b) how long in advance of a predicted close encounter should pilots request or execute a separation maneuver. The controller participants managed a busy Oakland air route traffic control sector with mixed commercial/general aviation and manned/UAS traffic, providing separation services, miles-in-trail restrictions and issuing traffic advisories. Controllers filled out post-scenario and post-simulation questionnaires, and metrics were collected on the acceptability of procedural options and temporal thresholds. The states of aircraft were also recorded when controllers issued traffic advisories. Subjective feedback indicated a strong preference for pilots to request maneuvers to remain well clear from intruder aircraft rather than deviate from their IFR clearance. Controllers also reported that maneuvering at 120 seconds until closest point of approach (CPA) was too early; maneuvers executed with less than 90 seconds until CPA were more acceptable. The magnitudes of the requested maneuvers were frequently judged to be too large, indicating a possible discrepancy between the quantitative UAS well clear standard and the one employed subjectively by manned pilots. The ranges between pairs of aircraft and the times to CPA at which traffic advisories were issued were used to construct empirical probability distributions of those metrics. Given these distributions, we propose that UAS pilots wait until an intruder aircraft is approximately 80 seconds to CPA or 6 nmi away before requesting a maneuver, and maneuver immediately if the intruder is within 60 seconds and 4 nmi. These thresholds should make the use of UAS detect and avoid systems compatible with current airspace procedures and controller expectations.

unmanned aircraft systems↗

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 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 NTRS2015

Analysis of UAS DAA Alerting in Fast-Time Simulations without DAA Mitigation

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 for DAA alerting 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 alerting systems. ACES simulations were conducted to study the performance of alerting systems proposed by the SC-228 DAA Alerting sub-group. Analysis included but was not limited to: 1) correct alert (and timeliness), 2) false alert (and severity and duration), 3) missed alert, and 4) probability of an alert type at the time of loss of well clear. The performance of DAA alerting systems when using intent vs. dead-reckoning for UAS ownship trajectories was also compared. The results will be used by SC-228 to inform decisions about the surveillance standards of UAS DAA systems and future requirements development and validation efforts.

alerting↗

NASA NTRS2015

Unmitigated ACES Simulation Supporting Draft DAA MOPS Alerting

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 for DAA alerting 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 alerting systems. ACES simulations were conducted to study the performance of an alerting scheme proposed by the SC-228 DAA Alerting sub-group. Analysis included but was not limited to: 1) correct alert (and their timeliness), 2) false alert (and their severity and duration), 3) missed alert, and 4) probability of an alert type at the time of loss of well clear. The results will be used by SC-228 to inform decisions about the alerting aspect of UAS DAA systems and future requirements development and validation efforts.

alerting↗

NASA NTRS2013

Separation-Compliant, Optimal Routing and Control of Scheduled Arrivals in a Terminal Airspace

We address the problem of navigating a set (fleet) of aircraft in an aerial route network so as to bring each aircraft to its destination at a specified time and with minimal distance separation assured between all aircraft at all times. The speed range, initial position, required destination, and required time of arrival at destination for each aircraft are assumed provided. Each aircraft's movement is governed by a controlled differential equation (state equation). The problem consists in choosing for each aircraft a path in the route network and a control strategy so as to meet the constraints and reach the destination at the required time. The main contribution of the paper is a model that allows to recast this problem as a decoupled collection of problems in classical optimal control and is easily generalized to the case when inertia cannot be neglected. Some qualitative insight into solution behavior is obtained using the Pontryagin Maximum Principle. Sample numerical solutions are computed using a numerical optimal control solver. The proposed model is first step toward increasing the fidelity of continuous time control models of air traffic in a terminal airspace. The Pontryagin Maximum Principle implies the polygonal shape of those portions of the state trajectories away from those states in which one or more aircraft pair are at minimal separation. The model also confirms the intuition that, the narrower the allowed speed ranges of the aircraft, the smaller the space of optimal solutions, and that an instance of the optimal control problem may not have a solution at all (i.e., no control strategy that meets the separation requirement and other constraints).

transportation network↗

NASA NTRS2012

Efficient Computation of Separation-Compliant Speed Advisories for Air Traffic Arriving in Terminal Airspace

A class of problems in air traffic management asks for a scheduling algorithm that supplies the air traffic services authority not only with a schedule of arrivals and departures, but also with speed advisories. Since advisories must be finite, a scheduling algorithm must ultimately produce a finite data set, hence must either start with a purely discrete model or involve a discretization of a continuous one. The former choice, often preferred for intuitive clarity, naturally leads to mixed-integer programs, hindering proofs of correctness and computational cost bounds (crucial for real-time operations). In this paper, a hybrid control system is used to model air traffic scheduling, capturing both the discrete and continuous aspects. This framework is applied to a class of problems, called the Fully Routed Nominal Problem. We prove a number of geometric results on feasible schedules and use these results to formulate an algorithm that attempts to compute a collective speed advisory, effectively finite, and has computational cost polynomial in the number of aircraft. This work is a first step toward optimization and models refined with more realistic detail.

Sadovsky, Alexander V.↗

NASA NTRS2010

A Concept for Robust, High Density Terminal Air Traffic Operations

This paper describes a concept for future high-density, terminal air traffic operations that has been developed by interpreting the Joint Planning and Development Office s vision for the Next Generation (NextGen) Air Transportation System and coupling it with emergent NASA and other technologies and procedures during the NextGen timeframe. The concept described in this paper includes five core capabilities: 1) Extended Terminal Area Routing, 2) Precision Scheduling Along Routes, 3) Merging and Spacing, 4) Tactical Separation, and 5) Off-Nominal Recovery. Gradual changes are introduced to the National Airspace System (NAS) by phased enhancements to the core capabilities in the form of increased levels of automation and decision support as well as targeted task delegation. NASA will be evaluating these conceptual technological enhancements in a series of human-in-the-loop simulations and will accelerate development of the most promising capabilities in cooperation with the FAA through the Efficient Flows Into Congested Airspace Research Transition Team.

Isaacson, Douglas R.↗

NASA NTRS2002

Development of Closed-Loop Simulation Methods for a Next-Generation Terminal Area Automation System

A next-generation air traffic decision support tool, known as the Active Final Approach Spacing Tool (aFAST), will generate heading, speed and altitude commands to achieve more precise separation of aircraft in the terminal area. The techniques used to analyze the performance of earlier generation decision support tools are not adequate to analyze the performance of aFAST. This paper summarizes the development of a new and innovative fully closed-loop testing method for aFAST. This method, called trajectory feedback testing, closes each aircraft's control loop inside of the aFAST scheduling algorithm. Validation of trajectory feedback testing by examination of the variation of aircraft time-of-arrival predictions between schedule updates and the variation of aircraft excess separation distances between simulation runs is presented.

Robinson, John E., III↗

NASA NTRS1996

Operational Test Results of the Final Approach Spacing Tool

A prototype decision support tool for terminal area air traffic controllers, referred to as the Final Approach Spacing Tool (FAST), was recently evaluated in operation with live air traffic at the Dallas/Fort Worth Terminal Radar Approach Control (TRACON) facility in the United States. Controllers utilized the FAST system's runway assignment and sequence advisories to manage and control arrival traffic during more than twenty five peak rush traffic periods. The system performed well resulting in capacity increases at the airport of 10-20% depending on weather and airport conditions. As a result of these tests, the US Federal Aviation Administration (FAA) is proceeding with plans to further develop the prototype FAST system for national deployment at five to ten TRACONs within the United States during the next five years. This paper will present the results of these tests including data on the FAST system impact on airport capacity, aircraft flight times in the terminal area, delay reduction, tower operations including ground movement, and human factors data including workload assessments.

Davis, Thomas J.↗