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At least 91 records · Page 5

En Route Descent Advisor Multi-Sector Planning Using Active and Provisional Controller Plans

As decision support tools are developed to support controllers in complex air traffic control environments, new approaches to maintaining situation awareness and managing traffic planning must be developed to handle the ever-increasing amounts of alerting and advisory data. Within high-density metering and other environments where flight path changes are the rule, not the exception, and where interactions between these changes are required, current trial planning approaches are limited by potential increases in workload. The Enroute Descent Advisor (EDA) is a set of decision support tool capabilities for managing high-density en route traffic subject to metering restrictions. The EDA system s novel approach builds aircraft plans from combinations of user intent data and builds controller plans from combinations of aircraft plans to effectively maintain situation awareness during traffic planning. By maintaining both active (current) and provisional (proposed) controller plans, EDA supports controllers in coordinated traffic planning both within and between sectors. Ultimately, EDA s multi-sector planning approach will facilitate a transition from current sector-oriented operations to a new trajectory-oriented paradigm, enabling new levels of efficiency and collaboration in air traffic control.

Vivona, Robert↗

Conflict Detection Using Variable Four-Dimensional Uncertainty Bounds to Control Missed Alerts

Decision-support tools for maintaining pairwise aircraft separation rely on conflict detection to alert the operator when the predicted trajectories of aircraft will result in a loss of separation. But aircraft frequently do not follow their predicted trajectories exactly. This can cause missed alerts and the failure of strategic separation procedures. We present a technique for modeling a bounded region of uncertainty around a four-dimensional predicted trajectory and an algorithm for detecting conflicts between trajectories modeled in this way that avoids missed alerts as long as the aircraft remain within the specified regions of uncertainty. In addition, we present an algorithm for detecting the intrusion of a trajectory modeled in this way into an area hazard modeled as a polygonal region. The size of the region of uncertainty can vary along the trajectory continually and independently in the along-path, cross-track, and vertical dimensions, providing an opportunity to reduce the likelihood of false alerts while protecting against typical prediction errors. The algorithm has been implemented in the Autonomous Operations Planner, a NASA Langley prototype decision support tool for airborne self-separation.

Karr, David A.↗

The Integrated Medical Model - Optimizing In-flight Space Medical Systems to Reduce Crew Health Risk and Mission Impacts

The Integrated Medical Model (IMM) is a decision support tool used by medical system planners and designers as they prepare for exploration planning activities of the Constellation program (CxP). IMM provides an evidence-based approach to help optimize the allocation of in-flight medical resources for a specified level of risk within spacecraft operational constraints. Eighty medical conditions and associated resources are represented in IMM. Nine conditions are due to Space Adaptation Syndrome. The IMM helps answer fundamental medical mission planning questions such as What medical conditions can be expected? What type and quantity of medical resources are most likely to be used?", and "What is the probability of crew death or evacuation due to medical events?" For a specified mission and crew profile, the IMM effectively characterizes the sequence of events that could potentially occur should a medical condition happen. The mathematical relationships among mission and crew attributes, medical conditions and incidence data, in-flight medical resources, potential clinical and crew health end states are established to generate end state probabilities. A Monte Carlo computational method is used to determine the probable outcomes and requires up to 25,000 mission trials to reach convergence. For each mission trial, the pharmaceuticals and supplies required to diagnose and treat prevalent medical conditions are tracked and decremented. The uncertainty of patient response to treatment is bounded via a best-case, worst-case, untreated case algorithm. A Crew Health Index (CHI) metric, developed to account for functional impairment due to a medical condition, provides a quantified measure of risk and enables risk comparisons across mission scenarios. The use of historical in-flight medical data, terrestrial surrogate data as appropriate, and space medicine subject matter expertise has enabled the development of a probabilistic, stochastic decision support tool capable of optimizing in-flight medical systems based on crew and mission parameters. This presentation will illustrate how to apply quantitative risk assessment methods to optimize the mass and volume of space-based medical systems for a space flight mission given the level of crew health and mission risk.

Kerstman, Eric↗

In-Flight Evaluation of the Traffic Aware Planner on the NASA HU-25A Guardian Aircraft

NASA’s Traffic Aware Planner (TAP) software is a research-prototype decision support tool that provides pilots with time- and fuel-saving route recommendations that optimize their current trajectory. The software runs on a first-of-a-kind system architecture onboard three aircraft in revenue service conducting operational evaluations with a major domestic airline. Therefore, significant NASA-internal testing is required prior to releasing the software to the partner airline. This paper describes a flight test plan that exercises the functionality of the TAP software in a representative operational environment, describes the system architecture developed and implemented for the NASA Langley HU-25A Guardian aircraft to support the test objectives, presents outcomes of the flight test campaign, and discusses use cases that demonstrate the value of flight testing for this activity.Research into flight path optimization of transport aircraft conducted by the National Aeronautics and SpaceAdministration (NASA) has produced an operational concept known as Traffic Aware Strategic Aircrew Requests(TASAR) [1, 2]. This near-term concept [3] provides the aircrew with a flight deck decision support tool known asthe Traffic Aware Planner (TAP). The TAP software leverages a growing number of information sources on the flightdeck to make time- and fuel-saving route optimization recommendations to the aircrew while en route. The aircrewcan then use the suggestions provided by the tool to make route change requests with a greater likelihood of acceptanceby air traffic control (ATC). Since TASAR is a concept intended for the current operational environment, it isintentionally designed to have no safety-critical impact or require any changes to current Federal AviationAdministration (FAA) rules and procedures [4, 5].The research prototype TAP system [6–8], explained further in Section III.C, continually incorporates up-to-dateaircraft state data from onboard avionics, as well as the latest position of surrounding traffic, the most recent windforecast, and the most recent convective weather forecast, in order to calculate candidate trajectory modifications thatimprove upon the current active route. These trajectories account for user-selectable objective functions [3] of reducedfuel burn, reduced flight time, or an airline-derived combination of factors known as trip cost. Previous analyses andsimulations have estimated substantial savings for airlines employing this technique within the U.S. National AirspaceSystem (NAS) [9–11]. Operational evaluations with Alaska Airlines seek to validate these projected benefits usingmeasured data while simultaneously providing benefits to the airline [12, 13].The TAP software has undergone a number of human-in-the-loop simulations [14] and flight test activities[15–17] in order to validate the operational concept, evaluate human factors considerations (e.g., workload, usability,distraction, etc.), and to assess the ability of the software to function in a representative operational environment (e.g.,connected to live avionics data, using in-flight internet connectivity, etc.). However, these simulations and flight testcampaigns did not account for the hardware architecture implemented on the three aircraft for Alaska Airlines’operational evaluations of the TAP software. Therefore, a need was identified to thoroughly test the functionality ofthe software in a similar hardware architecture to that of the partner airline’s aircraft. Information regarding testapparatus and environments used to evaluate TAP prior to testing on the HU-25A can be found in reference [18].A campaign of flight trials on a NASA aircraft, the HU-25A Guardian, was conducted to ensure that the researchprototype TAP system functions well in a configuration similar to the Alaska Airlines aircraft prior to deployment.This airborne, networked environment enables an assessment of the operational factors unique to the flight environment. Additionally, this activity evaluated the effectiveness and benefit of new TAP functionality andoperation in a relevant flight environment while allowing the rapid prototyping of new concepts and features.This paper is organized as follows: Section II discusses the details of the flight test plan, flight profiles, and theduties of personnel involved with conducting flight operations. Section III describes the test platform, avionicsequipage, and system architecture. Section IV presents a discussion of results, and Section V contains concludingremarks.

Underwood, Matthew C.↗

Development of a case tool to support decision based software development

A summary of the accomplishments of the research over the past year are presented. Achievements include: made demonstrations with DHC, a prototype supporting decision based software development (DBSD) methodology, for Paramax personnel at ODU; met with Paramax personnel to discuss DBSD issues, the process of integrating DBSD and Refinery and the porting process model; completed and submitted a paper describing DBSD paradigm to IFIP '92; completed and presented a paper describing the approach for software reuse at the Software Reuse Workshop in April 1993; continued to extend DHC with a project agenda, facility necessary for a better project management; completed a primary draft of the re-engineering process model for porting; created a logging form to trace all the activities involved in the process of solving the reengineering problem, and developed a primary chart with the problems involved by the reengineering process.

Wild, Christian J.↗

The Final Approach Spacing Tool (FAST)

The Final Approach Spacing Tool (FAST) is a decision support tool for terminal area (TRACON) air traffic controllers. FAST utilizes 4D trajectory synthesis, human performance modeling, and a graphical user interface to plan and advise efficient, conflict-free aircraft trajectories for arrival traffic. It increases airport capacity, reduces arrival delays, and reduces controller workload by issuing: sequence and runway advisories ("Passive" FAST) and speed and heading advisories ("Active" FAST). This paper discusses in detail the architecture of the system and operational tests done on the system.

Slattery, Rhonda↗

FATE: The drifting Fish Aggregating Device (dFAD) TrajEctory Modeling Tool for Marine Protected Area Management

Drifting fish aggregating devices (dFADs) routinely enter marine protected areas (MPAs) and may undermine MPA protections by drifting out of the MPA with the aggregated fish biomass, or grounding and damaging sensitive coral reef habitats. MPA managers must decide whether to deploy resources in response to dFAD intrusions. To address this issue, we propose to quantify dFAD activity in relation to ocean currents, fish biomass, and animal telemetry at Palmyra Atoll, part of the Pacific Remote Islands Marine National Monument in the central Pacific Ocean. Specifically, we propose to develop the dFAD TrajEctory Tool (FATE). FATE is an innovative decision support tool that will use NASA observations and numerical models to predict future dFAD trajectories and inform TNC and USFWS whether they should deploy tactical resources (boats, personnel) to monitor, intercept, or retrieve dFADs that have entered the Refuge. The objectives are to use NASA observational constraints on ocean winds and currents to assist with the ecological management of the Palmyra Atoll NWR and MPA. Specifically, we will deliver an operational software tool that quantifies the grounding risk associated with each tracked dFAD and decision support for grounding risk mitigation via intercept at sea. This project addresses Element 3.3: Protected area management of the 2022 Ecological Conservation Solicitation by developing a tool needed by MPA managers to make tactical and strategic decisions focused on improving the effectiveness of MPAs. By quantifying the riskof dFADs, this project will help monitor and better inform the deployment of tactical (ships/personnel) and strategic (legislative) resources to better manage MPAs. This project is a collaboration between The Nature Conservancy, who operate long-term projects within the Palmyra MPA, and the U.S. Fish and Wildlife Service, who have the authority to make decisions related to its management. We expect that the results of our proposal will benefit marine resources within the Palmyra MPA and could be transferred to other remote MPAs within the US and other island nations within the Pacific Ocean.

TrajEctory↗

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

This paper describes an experiment designed to compare the use of paper strips with the use of 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 study in a series of six HITL simulation experiments designed to evaluate a concept that provided advisories to the users. The RTC was designed to be used as a Decision Support Tool (DST) that provided advisories to ramp controllers regarding metering or pushback such that most of the delay was taken at the gate to save fuel and emissions. In addition to being a DST, an added benefit of the RTC is that it can provide real-time updates of flight data, airport and airspace status to the controller including Traffic Management Initiatives (TMI). The RTC was designed as new user interface that displays virtual strips on a terminal map drawn on a 27-inch touch screen monitor. The RTC was used in some conditions of the experiment by ramp controllers in place of paper strips and paper maps in the HITL environment. In other conditions the controllers were given paper strips and paper maps similar to what they currently use at Charlotte Douglas International Airport (CLT). The study described here, evaluated the use of the virtual strips displayed on the RTC as compared to the use of paper strips and paper map, using current ramp tower controllers at CLT as participants. The research question being asked was - How does management of ramp traffic affect user workload and usability ratings while using RTC to manage traffic in the ramp verses using paper strips? Workload for our purposes is defined by four components of the NASA-TLX (Task Load Index). Usability was assessed with two sets of usability questions - One set of usability questions addressed traffic management performance and the other set addressed issues of resources and efficiency. Both Post Run and Post Study questionnaire responses were gathered and the results were analyzed to assess controller workload and usability ratings under both conditions, virtual strips shown on RTC and Paper Strips. The results indicate that controllers perceived lower workload while using virtual strips displayed on RTC to manage ramp traffic. Usability ratings for Traffic management performance questions are lower in the virtual strip/RTC condition than in the paper strip condition showing a preference for RTC over Paper. Usability ratings for Resources and efficiency questions show mixed results. Additionally, the Post Study Questions show preference for RTC over paper strips. Results of this data analysis will be presented in this paper. This DST evaluation was an important step in researching and improving the tool, which was planned to be deployed in the field.

Aviation Decision Support Tools↗

The Application of NASA Remote Sensing Technology to Human Health

With the help of satellites, the Earth's environment can be monitored from a distance. Earth observing satellites and sensors collect data and survey patterns that supply important information about the environment relating to its affect on human health. Combined with ground data, such patterns and remote sensing data can be essential to public health applications. Remote sensing technology is providing information that can help predict factors that affect human health, such as disease, drought, famine, and floods. A number of public health concerns that affect Earth's human population are part of the current National Aeronautics and Space Administration (NASA) Earth Science Applications Plan to provide remotely gathered data to public health decision-makers to aid in forming and implementing policy to protect human health and preserve well-being. These areas of concern are: air quality; water quality; weather and climate change; infectious, zoonotic, and vector-borne disease; sunshine; food resource security; and health risks associated with the built environment. Collaborations within the Earth Science Applications Plan join local, state, national, or global organizations and agencies as partners. These partnerships engage in projects that strive to understand the connection between the environment and health. The important outcome is to put this understanding to use through enhancement of decision support tools that aid policy and management decisions on environmental health risks. Future plans will further employ developed models in formats that are compatible and accessible to all public health organizations.

Watts, C. T.↗

Overview: Spot and Runway Departure Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for DallasFt. Worth International Airport. The presentation also explains the latest status of NASA's current surface research through a collaboration with an airline partner. The presentation concludes with a discussion on other on-going as well as future surface research.

decision support tool↗

Analysis of ETMS Data Quality for Traffic Flow Management Decisions

The data needed for air traffic flow management decision support tools is provided by the Enhanced Traffic Management System (ETMS). This includes both the tools that are in current use and the ones being developed for future deployment. Since the quality of decision support provided by all these tools will be influenced by the quality of the input ETMS data, an assessment of ETMS data quality is needed. Motivated by this desire, ETMS data quality is examined in this paper in terms of the unavailability of flight plans, deviation from the filed flight plans, departure delays, altitude errors and track data drops. Although many of these data quality issues are not new, little is known about their extent. A goal of this paper is to document the magnitude of data quality issues supported by numerical analysis of ETMS data. Guided by this goal, ETMS data for a 24-hour period were processed to determine the number of aircraft with missing flight plan messages at any given instant of time. Results are presented for aircraft above 18,000 feet altitude and also at all altitudes. Since deviation from filed flight plan is also a major cause of trajectory-modeling errors, statistics of deviations are presented. Errors in proposed departure times and ETMS-generated vertical profiles are also shown. A method for conditioning the vertical profiles for improving demand prediction accuracy is described. Graphs of actual sector counts obtained using these vertical profiles are compared with those obtained using the Host data for sectors in the Fort Worth Center to demonstrate the benefit of preprocessing. Finally, results are presented to quantify the extent of data drops. A method for propagating track positions during ETMS data drops is also described.

Chatterji, Gano B.↗

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↗

A Comparison of Satellite Based, Modeled Derived Daily Solar Radiation Data with Observed Data for the Continental US

Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these tools. Daily solar radiation (SRAD) data are especially problematic because the instruments require electronic integrators, accurate sensors are expensive, and calibration standards are seldom available. The Prediction Of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov) project at the NASA Langley Research Center estimates daily solar radiation based on data that are derived from satellite observations of outgoing visible radiances and atmospheric parameters based upon satellite observations and assimilation models. The solar data are available for a global 1 degree x 1 degree coordinate grid. SRAD can also be estimated based on attenuation of extraterrestrial radiation (Q0) using daily temperature and rainfall data to estimate the optical thickness of the atmosphere. This study compares daily solar radiation data from NASA/POWER (SRADNP) with instrument readings from 295 stations (SRADOB), as well as with values that were estimated with the WGENR solar generator. WGENR was used both with daily temperature and precipitation records from the stations reporting solar data and records from the NOAA Cooperative Observer Program (COOP), thus providing two additional sources of solar data, SRADWG and SRADCO. Values of SRADNP for different grid cells consistently showed higher correlations (typically 0.85 to 0.95) with SRADOB data than did SRADWG or SRADCO for sites within the corresponding cells. Mean values of SRADOB, SRADWG and SRADNP for sites within a grid cell usually were within 1 MJm-2d-1 of each other, but NASA/POWER values averaged 1.1 MJm-2d-1 lower than SRADOB. The magnitude of this bias was greater at lower latitudes and during summer months and may be at least partially explained by assumptions in ambient aerosol properties. Overall, the NASA/POWER solar radiation data are a promising resource for regional modeling studies where realistic accounting of historic variation is required.

White, Jeffrey W.↗

Coordinating complex decision support activities across distributed applications

Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

Adler, Richard M.↗

Impact of ATD-2 Tools on Human Factors Metrics at Charlotte Douglas International Airport

New decision support tools were introduced at Charlotte Douglas International Airport (CLT) as part of NASA’s Air Traffic Demonstration 2 (ATD-2) project. ATD-2 is based on concepts which enable integrated arrival, departures, and surface (IADS) operations in a metroplex environment. Metrics on environmental benefits from ATD-2’s surface metering at CLT have shown impressive reductions in fuel consumption and CO2 emissions. Questions have remained on 1) the human factors impact of these new ATD-2 tools and surface metering and 2) the users’ perceptions of how these tools affect operations. To address these questions, post-bank surveys were designed for the four types of users of the new tools at CLT: Ramp Controllers, Ramp Managers, Tower Traffic Management Coordinators (TMCs) and Terminal Radar Approach Control (TRACON) TMCs. These surveys were administered during five-day blocks at three different times. Three types of banks were compared: No ATD-2 tool use, ATD-2 tool use, and ATD-2 use plus surface metering. Results indicate that higher workload or decreased situation awareness was not significantly associated with ATD-2 tool use more than no ATD-2 tool use--in fact for many users the opposite was true. Also, acceptability and operational efficiency measures indicate that the users did not perceive that banks with ATD-2 tools were significantly less acceptable or less efficient than banks without ATD-2 tools.

Airspace Technology Demonstration 2↗

Impact of ATD-2 Tools on Human Factor Metrics at Charlotte Douglas International Airport

New decision support tools were introduced at Charlotte Douglas International Airport (CLT) as part of NASA’s Air Traffic Demonstration 2 (ATD-2) project. ATD-2 is based on concepts which enable integrated arrival, departures, and surface (IADS) operations in a metroplex environment. Metrics on environmental benefits from ATD-2’s surface metering at CLT have shown impressive reductions in fuel consumption and CO2 emissions. Questions have remained on 1) the human factors impact of these new ATD-2 tools and surface metering and 2) the users’ perceptions of how these tools affect operations. To address these questions, post-bank surveys were designed for the four types of users of the new tools at CLT: Ramp Controllers, Ramp Managers, Tower Traffic Management Coordinators (TMCs) and Terminal Radar Approach Control (TRACON) TMCs. These surveys were administered during five-day blocks at three different times. Three types of banks were compared: No ATD-2 tool use, ATD-2 tool use, and ATD-2 use plus surface metering. Results indicate that higher workload or decreased situation awareness was not significantly associated with ATD-2 tool use more than no ATD-2 tool use--in fact for many users the opposite was true. Also, acceptability and operational efficiency measures indicate that the users did not perceive that banks with ATD-2 tools were significantly less acceptable or less efficient than banks without ATD-2 tools.

Bonny K Parke↗

Romie: A Domain-Independent Tool for Computer-Aided Robust Operations Management

Romie is a decision support tool based on AI's latest advances in the domain of robust scheduling. Unlike all its predecessors, the tool allows to (i) visually model the operational problem and context entirely (ii) optimize to find near-optimal schedules while taking uncertainty into account and deals with (iii) a combination of various {key performance indicators (KPIs). It comes with a web user interface. Part or all of the modelled activities may be associated to random variables describing their stochastic durations, in order to produce schedules that are robust w.r.t. temporal uncertainty. Hence, depending on the pursued KPIs, the schedules maximize a combination of the following terms: the probability of satisfying the problem constraints, the expected return/efficiency, the expected outcome quality, and even the operators' wellness by minimizing its expected extra-hours. Initially developed for spatial exploration and demonstration in the context of Mars analog missions, this versatile tool is here applied to operations management in both biotechnology manufacturing and robots parametrization in a cave exploration context.

Chien, Steve A.↗