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At least 163 records · Page 9

Evaluation of a Dynamic Weather-Avoidance Rerouting Tool in Adjacent-Center Arrival Metering

Dynamic Reroutes for Arrivals in Weather (DRAW) is a NASA-developed decision-support tool for Traffic Management Coordinators (TMCs) at the Federal Aviation Administration's Air Route Traffic Control Centers ("Centers"). DRAW proposes weather-avoidance reroutes for en route arrival flights subject to metering restrictions when transitioning into a busy terminal airspace. The prior DRAW study demonstrated that TMCs' use of DRAW promotes earlier reroutes of arrivals, and reduces the number of routes conflicting with weather in the Center. The present paper focuses on how DRAW benefits metering delivery accuracy when schedule freeze horizon distance was altered. A human-in-the-loop simulation was conducted at NASA Ames Research Center in October-November 2018, where retired TMCs and controllers performed simulated metering operations for southeast arrivals through the Atlanta and Jacksonville Centers to the Hartsfield-Jackson Atlanta International Airport during convective weather periods. Results demonstrated that DRAW use reduced the frequency of manual adjustments of Scheduled Times of Arrival and lowered TMC workload. DRAW use also made the metering accuracy, the number of reroute amendments after the freeze horizon, and the en route sector controller workload more robust to the effect of different freeze horizon distance.

Hayashi, Miwa↗

Evaluation of a Dynamic Weather-Avoidance Rerouting Tool in Adjacent-Center Arrival Metering

Dynamic Reroutes for Arrivals in Weather (DRAW) is a NASA-developed decision-support tool for Traffic Management Coordinators (TMCs) at the Federal Aviation Administration's Air Route Traffic Control Centers ("Centers"). DRAW proposes weather-avoidance reroutes for en route arrival flights subject to metering restrictions when transitioning into a busy terminal airspace. The prior DRAW study demonstrated that TMCs' use of DRAW promotes earlier reroutes of arrivals, and reduces the number of routes conflicting with weather in the Center. The present paper focuses on how DRAW benefits metering delivery accuracy when schedule freeze horizon distance was altered. A human-in-the-loop simulation was conducted at NASA Ames Research Center in October-November 2018, where retired TMCs and controllers performed simulated metering operations for southeast arrivals through the Atlanta and Jacksonville Centers to the Hartsfield-Jackson Atlanta International Airport during convective weather periods. Results demonstrated that DRAW use reduced the frequency of manual adjustments of Scheduled Times of Arrival and lowered TMC workload. DRAW use also made the metering accuracy, the number of reroute amendments after the freeze horizon, and the en route sector controller workload more robust to the effect of different freeze horizon distance.

Air Traffic Management (ATM)↗

Evaluation of Usability and Workload Associated with Paper Strips as Compared to Virtual Flight Strips Used for Ramp Operations

This paper describes a study comparing the use of paper strips with virtual flight strips depicted on a new user interface, the Ramp Traffic Console (RTC), designed for use by ramp controllers to be used in place of paper strips. A Human-In-the-Loop (HITL) experiment was performed as the fifth in a series of six HITL simulation studies designed to evaluate a pushback Decision Support Tool (DST) concept for Charlotte Douglas International Airport (CLT). Workload and usability were assessed in post-run and post-study questionnaires. In the RTC virtual flight strip condition, post-run questionnaire results show lower workload ratings across all aspects of workload; additionally a trend is found toward increased usability ratings. Post-study questionnaire results indicate a preference for RTC over paper strips. Additional research is suggested with more training runs and a greater number of participants to increase statistical power. It is also suggested that this new technology be re-evaluated as a part of the ATD-2 (Airspace Technology Demonstration 2) field testing activities.

Human Factors↗

Spaceflight Medical Evacuation Risk Assessment Principles - A Qualitative Investigation

BACKGROUND Future human space exploration beyond Low Earth Orbit (LEO) will require innovative solutions in many areas, primarily those that provide direct medical support to crew on long-duration missions and optimize their health and performance. The associated challenges therein will be numerous, including but not necessarily limited to extended one-way or "asynchronous" communication delays, minimal to non-existent resupply, and a prolonged transit time to "definitive care" ranging from 3-days to 9-months. At the same time, long-duration exploration spacecraft and crew will face restrictions on mass, power, volume, and data far more significant than that seen in current LEO settings. Given these limitations, medical risk assessment is of primary importance, especially evaluating the implications of a medical evacuation of an ill or injured crewmember. Such evacuations are complicated, potentially dangerous, and well may be impossible in certain phases of the mission. Regardless, such issues must be weighed against the risks of the injured crew remaining aboard a spacecraft with limited medical resources. OBJECTIVE This qualitative study drew from the experiences of subject matter experts (SMEs) in spaceflight and appropriate analog environments (i.e., military, disaster, and extreme environment fields) to identify unique principles common amongst medical evacuation considerations helpful in informing future risk assessment tools. Appropriate analog environments included austere operational settings where multiple factors (weather, logistics/limited resupply, denied/extreme environments, and patient condition) resulted in a limited ability to provide definitive local medical care. The fundamental principles in question revolved around scenarios where evacuation became a complicating yet necessary consideration and where life-threatening medical concerns had to be weighed against critical mission objective(s). The primary authors collected semi-structured data gathered through in-depth interviews with 16 subject matter experts (SMEs). Interview questions investigated how these SMEs consider and weigh the attendant risks present in medical evacuation scenarios. Among the critical questions posed were those that sought to understand how the SME balanced the challenges and requirements of medical evacuation (or keeping an injured patient "on-site" aka: "prolonged field care") against the evacuation operation's risks on impacting overarching mission success. The team analyzed interview transcripts for common themes and principles using the qualitative methods of thematic analysis based on consensus, co-occurrence, and comparison. As a result, nine primary risk consideration themes and nine contributing factor themes emerged, all of which will ideally inform future medical evacuation decision-making tools and operational decision-making for exploration class missions. Specific aims for this study included: 1. Identification of common principles used to assess risks and benefits of medical evacuations in extreme environments 2. Identification of common points of friction or complication and challenges in extreme environment evacuations

A T Almand↗

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗

Transitioning NPOESS Data to Weather Offices: The SPoRT Paradigm with EOS Data

Real-time satellite information provides one of many data sources used by NWS weather forecast offices (WFOs) to diagnose current weather conditions and to assist in short-term forecast preparation. While GOES satellite data provides relatively coarse spatial resolution coverage of the continental U.S. on a 10-15 minute repeat cycle, polar orbiting imagery has the potential to provide snapshots of weather conditions at high-resolution in many spectral channels. Additionally, polar orbiting sounding data can provide additional information on the thermodynamic structure of the atmosphere in data sparse regions of at asynoptic observation times. The NASA Short-term Prediction Research and Transition (SPoRT) project has demonstrated the utility of polar orbiting MODIS and AIRS data on the Terra and Aqua satellites to improve weather diagnostics and short-term forecasting on the regional and local scales. SPoRT scientists work directly forecasters at selected WFOS in the Southern Region (SR) to help them ingest these unique data streams into their AWIPS system, understand how to use the data (through on-site and distance learn techniques), and demonstrate the utility of these products to address significant forecast problems. This process also prepares forecasters for the use of similar observational capabilities from NPOESS operational sensors. NPOESS environmental data records (EDRs) from the Visible 1 Infrared Imager I Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrlS) and Advanced Technology Microwave Sounder (ATMS) instruments and additional value-added products produced by NESDIS will be available in near real-time and made available to WFOs to extend their use of NASA EOS data into the NPOESS era. These new data streams will be integrated into the NWs's new AWIPS II decision support tools. The AWIPS I1 system to be unveiled in WFOs in 2009 will be a JAVA-based decision support system which preserves the functionality of the existing systems and offers unique development opportunities for new data sources and applications in the Service Orientated Architecture ISOA) environment. This paper will highlight some of the SPoRT activities leading to the integration of VllRS and CrIS/ATMS data into the display capabilities of these new systems to support short-term forecasting problems at WFOs.

Jedlovec, Gary↗

Evaluation of Flight Deck-Based Interval Management Crew Procedure Feasibility

Air traffic demand is predicted to increase over the next 20 years, creating a need for new technologies and procedures to support this growth in a safe and efficient manner. The National Aeronautics and Space Administration's (NASA) Air Traffic Management Technology Demonstration - 1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The integration of these technologies will increase throughput, reduce delay, conserve fuel, and minimize environmental impacts. The ground-based tools include Traffic Management Advisor with Terminal Metering for precise time-based scheduling and Controller Managed Spacing decision support tools for better managing aircraft delay with speed control. The core airborne technology in ATD-1 is Flight deck-based Interval Management (FIM). FIM tools provide pilots with speed commands calculated using information from Automatic Dependent Surveillance - Broadcast. The precise merging and spacing enabled by FIM avionics and flight crew procedures will reduce excess spacing buffers and result in higher terminal throughput. This paper describes a human-in-the-loop experiment designed to assess the acceptability and feasibility of the ATD-1 procedures used in a voice communications environment. This experiment utilized the ATD-1 integrated system of ground-based and airborne technologies. Pilot participants flew a high-fidelity fixed base simulator equipped with an airborne spacing algorithm and a FIM crew interface. Experiment scenarios involved multiple air traffic flows into the Dallas-Fort Worth Terminal Radar Control airspace. Results indicate that the proposed procedures were feasible for use by flight crews in a voice communications environment. The delivery accuracy at the achieve-by point was within +/- five seconds and the delivery precision was less than five seconds. Furthermore, FIM speed commands occurred at a rate of less than one per minute, and pilots found the frequency of the speed commands to be acceptable at all times throughout the experiment scenarios.

Wilson, Sara R.↗

Remote Sensing: A valuable tool in the Forest Service decision making process

Forest Service studies for integrating remotely sensed data into existing information systems highlight a need to: (1) re-examine present methods of collecting and organizing data, (2) develop an integrated information system for rapidly processing and interpreting data, (3) apply existing technological tools in new ways, and (4) provide accurate and timely information for making right management decisions. The Forest Service developed an integrated information system using remote sensors, microdensitometers, computer hardware and software, and interactive accessories. Their efforts substantially reduce the time it takes for collecting and processing data.

Stanton, F. L.↗

PC4CAST: A tool for DSN load forecasting and capacity planning

Effectively planning the use and evolution of the Deep Space Network (DSN) is a complex problem involving many parameters. The tool that models many of these complexities, yet requires simple structured inputs and provides concise easy-to-understand metrics to aid in the planning process is discussed. The tool, PC4CAST, is used for both load forecasting (predicting how well planned that DSN resources meet expected demand) and as a decision support tool in the capacity-planning process (determining the relative benefits of capacity expansion options). It is now in use in the TDA Planning Office, has been used in numerous studies, and is also being used by the JPL Multimission Operations System Office (MOSO) as an integral part of Resource Allocation Team activities. Experience using the tool has helped to identify additional requirements that will further improve the planning process, which can be met by future PC4CAST versions.

Loyola, S. J.↗

Intelligent Medical Systems for Aerospace Emergency Medical Services

The purpose of this project is to develop a portable, hands free device for emergency medical decision support to be used in remote or confined settings by non-physician providers. Phase I of the project will entail the development of a voice-activated device that will utilize an intelligent algorithm to provide guidance in establishing an airway in an emergency situation. The interactive, hands free software will process requests for assistance based on verbal prompts and algorithmic decision-making. The device will allow the CMO to attend to the patient while receiving verbal instruction. The software will also feature graphic representations where it is felt helpful in aiding in procedures. We will also develop a training program to orient users to the algorithmic approach, the use of the hardware and specific procedural considerations. We will validate the efficacy of this mode of technology application by testing in the Johns Hopkins Department of Emergency Medicine. Phase I of the project will focus on the validation of the proposed algorithm, testing and validation of the decision making tool and modifications of medical equipment. In Phase 11, we will produce the first generation software for hands-free, interactive medical decision making for use in acute care environments.

Epler, John↗

Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis

The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.

Eisenhawer, S. W.↗

En route Spacing Tool: Efficient Conflict-free Spacing to Flow-Restricted Airspace

This paper describes the Air Traffic Management (ATM) problem within the U.S. of flow-restricted en route airspace, an assessment of its impact on airspace users, and a set of near-term tools and procedures to resolve the problem. The FAA is committed, over the next few years, to deploy the first generation of modem ATM decision support tool (DST) technology under the Free-Flight Phase-1 (FFp1) program. The associated en route tools include the User Request Evaluation Tool (URET) and the Traffic Management Advisor (TMA). URET is an initial conflict probe (ICP) capability that assists controllers with the detection and resolution of conflicts in en route airspace. TMA orchestrates arrivals transitioning into high-density terminal airspace by providing controllers with scheduled times of arrival (STA) and delay feedback advisories to assist with STA conformance. However, these FFPl capabilities do not mitigate the en route Miles-In-Trail (MIT) restrictions that are dynamically applied to mitigate airspace congestion. National statistics indicate that en route facilities (Centers) apply Miles-In-Trail (MIT) restrictions for approximately 5000 hours per month. Based on results from this study, an estimated 45,000 flights are impacted by these restrictions each month. Current-day practices for implementing these restrictions result in additional controller workload and an economic impact of which the fuel penalty alone may approach several hundred dollars per flight. To mitigate much of the impact of these restrictions on users and controller workload, a DST and procedures are presented. The DST is based on a simple derivative of FFP1 technology that is designed to introduce a set of simple tools for flow-rate (spacing) conformance and integrate them with conflict-probe capabilities. The tool and associated algorithms are described based on a concept prototype implemented within the CTAS baseline in 1995. A traffic scenario is used to illustrate the controller's use of the tool, and potential display options are presented for future controller evaluation.

Green, S.↗

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

Otterstatter, Matthew R.↗

Clinical Outcome Metrics for Optimization of Robust Training

Introduction: The emphasis of this research is on the Human Research Program (HRP) Exploration Medical Capability's (ExMC) "Risk of Unacceptable Health and Mission Outcomes Due to Limitations of In-Flight Medical Capabilities." Specifically, this project aims to contribute to the closure of gap ExMC 2.02: We do not know how the inclusion of a physician crew medical officer quantitatively impacts clinical outcomes during exploration missions. The experiments are specifically designed to address clinical outcome differences between physician and non-physician cohorts in both near-term and longer-term (mission impacting) outcomes. Methods: Medical simulations will systematically compare success of individual diagnostic and therapeutic procedure simulations performed by physician and non-physician crew medical officer (CMO) analogs using clearly defined short-term (individual procedure) outcome metrics. In the subsequent step of the project, the procedure simulation outcomes will be used as input to a modified version of the NASA Integrated Medical Model (IMM) to analyze the effect of the outcome (degree of success) of individual procedures (including successful, imperfectly performed, and failed procedures) on overall long-term clinical outcomes and the consequent mission impacts. The procedures to be simulated are endotracheal intubation, fundoscopic examination, kidney/urinary ultrasound, ultrasound-guided intravenous catheter insertion, and a differential diagnosis exercise. Multiple assessment techniques will be used, centered on medical procedure simulation studies occurring at 3, 6, and 12 months after initial training (as depicted in the following flow diagram of the experiment design). Discussion: Analysis of procedure outcomes in the physician and non-physician groups and their subsets (tested at different elapsed times post training) will allow the team to 1) define differences between physician and non-physician CMOs in terms of both procedure performance (pre-IMM analysis) and overall mitigation of the mission medical impact (IMM analysis); 2) refine the procedure outcome and clinical outcome metrics themselves; 3) refine or develop innovative medical training products and solutions to maximize CMO performance; and 4) validate the methods and products of this experiment for operational use in the planning, execution, and quality assurance of the CMO training process The team has finalized training protocols and developed a software training/testing tool in collaboration with Butler Graphics (Detroit, MI). In addition to the "hands on" medical procedure modules, the software includes a differential diagnosis exercise (limited clinical decision support tool) to evaluate the diagnostic skills of participants. Human subject testing will occur over the next year.

Ebert, D.↗

Method for optimizing resource allocation in a government organization

The managers in Federal agencies are challenged to control the extensive activities in government and still provide high-quality products and services to the American taxpayers. Considering today's complex social and economic environment and the $3.8 billion daily cost of operating the Federal Government, it is evident that there is a need to develop decision-making tools for accurate resource allocation and total quality management. The goal of this thesis is to provide a methodical process that will aid managers in Federal Government to make budgetary decisions based on the cost of services, the agency's objectives, and the customers' perception of the agency's product. A general resource allocation procedure was developed in this study that can be applied to any government organization. A government organization, hereafter the 'organization,' is assumed to be a multidivision enterprise. This procedure was applied to a small organization for the proof of the concept. This organization is the Technical Services Directorate (TSD) at the NASA Lewis Research Center in Cleveland, Ohio. As part of the procedure, a nonlinear programming model was developed to account for the resources of the organization, the outputs produced by the organization, the decision-maker's views, and the customers' satisfaction with the organization. The information on the resources of the organization was acquired from current budget levels of the organization and the human resources assigned to the divisions. The outputs of the organization were defined and measured by identifying metrics that assess the outputs, the most challenging task in this study. The decision-maker's views are represented in the model as weights assigned to the various outputs and were quantified by using the analytic hierarchy process. The customer's opinions regarding the outputs of the organization were collected through questionnaires that were designed for each division individually. Following the philosophy of total quality management, information on customers' satisfaction is presented in the model as the quality of output. The model is a nonlinear one whose objective is to maximize customers' satisfaction such that the total cost of operation does not exceed the organization's budget. This model represents a structured approach or policy mechanism, at the agency level, to make capital investment decisions based on the priorities of the agency and the quality of outputs. This procedure applied to TSD resulted in a resources allocation scheme that was reasonable and acceptable to the decision-makers and, as expected, dependent on the assumptions and accuracy of the data used in the model.

Afarin, James↗

Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

Strategy↗

Using Risk Assessment Methodologies to Meet Management Objectives

Corporate and program objectives focus on desired performance and results. Management decisions that affect how to meet these objectives now involve a complex mix of: technology, safety issues, operations, process considerations, employee considerations, regulatory requirements, financial concerns and legal issues. Risk Assessments are a tool for decision makers to understand potential consequences and be in a position to reduce, mitigate or eliminate costly mistakes or catastrophic failures. Using a risk assessment methodology is only a starting point. A risk assessment program provides management with important input in the decision making process. A pro-active organization looks to the future to avoid problems, a reactive organization can be blindsided by risks that could have been avoided. You get out what you put in, how useful your program is will be up to the individual organization.

DeMott, D. L.↗