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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

MoCog1: A computer simulation of recognition-primed human decision making, considering emotions

The successful results of the first stage of a research effort to develop a versatile computer model of motivated human cognitive behavior are reported. Most human decision making appears to be an experience-based, relatively straightforward, largely automatic response to situations, utilizing cues and opportunities perceived from the current environment. The development, considering emotions, of the architecture and computer program associated with such 'recognition-primed' decision-making is described. The resultant computer program (MoCog1) was successfully utilized as a vehicle to simulate earlier findings that relate how an individual's implicit theories orient the individual toward particular goals, with resultant cognitions, affects, and behavior in response to their environment.

Gevarter, William B.↗
NASA NTRS2001

Aviation System Safety and Pilot Risk Perception: Implications for Enhancing Decision-Making Skills

This research explores risk perception in a defined population of flight instructors and the implications of these views for flight training. Flight instructors and students engaged in collegiate aviation flight training were interviewed for this qualitative study. Thirty-three percent of the instructors interviewed reported that flying is not a risky activity. This is important because research identifies risk perception as one factor influencing instructional choices. These choices can then impact the subsequent decision-making processes of flight students. Facilitating pilot decision-making through the use of an appropriate type of learning that incorporates the modeling of consensually validated cognitive procedures and risk management processes is discussed.

Green, Mavis F.↗
NASA NTRS1982

Supervision of dynamic systems: Monitoring, decision-making and control

Effects of task variables on the performance of the human supervisor by means of modelling techniques are discussed. The task variables considered are: The dynamics of the system, the task to be performed, the environmental disturbances and the observation noise. A relationship between task variables and parameters of a supervisory model is assumed. The model consists of three parts: (1) The observer part is thought to be a full order optimal observer, (2) the decision-making part is stated as a set of decision rules, and (3) the controller part is given by a control law. The observer part generates, on the basis of the system output and the control actions, an estimate of the state of the system and its associated variance. The outputs of the observer part are then used by the decision-making part to determine the instants in time of the observation actions on the one hand and the controls actions on the other. The controller part makes use of the estimated state to derive the amplitude(s) of the control action(s).

White, T. N.↗
NASA NTRS2012

Using NASA Environmental Data to Enhance Public Health Decision Making

The Universities Space Research Association at the NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this collaboration are to develop high-quality spatial data sets of environmental variables, and deliver the data sets and associated analyses to local, state and federal end-user groups. These data can be linked spatially and temporally to public health data, such as mortality and disease morbidity, for further analysis and decision making. Three daily environmental data sets have been developed for the conterminous U.S. on different spatial resolutions for the time period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be made available to public health professionals, researchers and the general public through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer reviewed publications. To date, two of the data sets have been released to the public in CDC WONDER, Daily Air Temperature and Heat Index for years 1979-2010, and Daily Fine Particulate Matter (PM2.5) air quality measures for years 2003-2008. These data in CDC WONDER can be aggregated to the county-level, state-level, or regional-level as per users need and downloaded in tabular, graphical, and map formats. The summary statistical output are available to web and app developers via the WONDER Application Programming Interface (API). The linkage of these data with the CDC WONDER system provides a significant addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER online system. It also substantially expands public access to NASA environmental data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗
NASA NTRS1990

Pilot interaction with automated airborne decision making systems

Ways in which computers can aid the decision making of an human operator of an aerospace system are investigated. The approach taken is to aid rather than replace the human operator, because operational experience has shown that humans can enhance the effectiveness of systems. As systems become more automated, the role of the operator has shifted to that of a manager and problem solver. This shift has created the research area of how to aid the human in this role. Published research in four areas is described. A discussion is presented of the DC-8 flight simulator at Georgia Tech.

Hammer, John M.↗
NASA NTRS1990

Manual and computer-aided materials selection for industrial production: An exercise in decision making

Students are introduced to methods and concepts for systematic selection and evaluation of materials which are to be used to manufacture specific products in industry. For this laboratory exercise, students are asked to work in groups to identify and describe a product, then to proceed through the process to select a list of three candidates to make the item from. The exercise draws on knowledge of mechanical, physical, and chemical properties, common materials test techniques, and resource management skills in finding and assessing property data. A very important part of the exercise is the students' introduction to decision making algorithms, and learning how to apply them to a complex decision making process.

Bates, Seth P.↗
NASA NTRS2014

Providing Global Change Information for Decision-Making: Capturing and Presenting Provenance

Global change information demands access to data sources and well-documented provenance to provide evidence needed to build confidence in scientific conclusions and, in specific applications, to ensure the information's suitability for use in decision-making. A new generation of Web technology, the Semantic Web, provides tools for that purpose. The topic of global change covers changes in the global environment (including alterations in climate, land productivity, oceans or other water resources, atmospheric composition and or chemistry, and ecological systems) that may alter the capacity of the Earth to sustain life and support human systems. Data and findings associated with global change research are of great public, government, and academic concern and are used in policy and decision-making, which makes the provenance of global change information especially important. In addition, since different types of decisions benefit from different types of information, understanding how to capture and present the provenance of global change information is becoming more of an imperative in adaptive planning.

provenance tracking↗
NASA NTRSDate not supplied

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya N Das↗
NASA NTRS2022

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya Das↗
NASA NTRS2004

Propulsion Airframe Aeroacoustics Technology Evaluation and Selection Using a Multi-Attribute Decision Making Process and Non-Deterministic Design

The Systems Analysis Branch at NASA Langley Research Center has investigated revolutionary Propulsion Airframe Aeroacoustics (PAA) technologies and configurations for a Blended-Wing-Body (BWB) type aircraft as part of its research for NASA s Quiet Aircraft Technology (QAT) Project. Within the context of the long-term NASA goal of reducing the perceived aircraft noise level by a factor of 4 relative to 1997 state of the art, major configuration changes in the propulsion airframe integration system were explored with noise as a primary design consideration. An initial down-select and assessment of candidate PAA technologies for the BWB was performed using a Multi-Attribute Decision Making (MADM) process consisting of organized brainstorming and decision-making tools. The assessments focused on what effect the PAA technologies had on both the overall noise level of the BWB and what effect they had on other major design considerations such as weight, performance and cost. A probabilistic systems analysis of the PAA configurations that presented the best noise reductions with the least negative impact on the system was then performed. Detailed results from the MADM study and the probabilistic systems analysis will be published in the near future.

Burg, Cecile M.↗
NASA NTRS2004

Systems Engineering Techniques for ALS Decision Making

The Advanced Life Support (ALS) Metric is the predominant tool for predicting the cost of ALS systems. Metric goals for the ALS Program are daunting, requiring a threefold increase in the ALS Metric by 2010. Confounding the problem, the rate new ALS technologies reach the maturity required for consideration in the ALS Metric and the rate at which new configurations are developed is slow, limiting the search space and potentially giving the perspective of a ALS technology, the ALS Metric may remain elusive. This paper is a sequel to a paper published in the proceedings of the 2003 ICES conference entitled, "Managing to the metric: an approach to optimizing life support costs." The conclusions of that paper state that the largest contributors to the ALS Metric should be targeted by ALS researchers and management for maximum metric reductions. Certainly, these areas potentially offer large potential benefits to future ALS missions; however, the ALS Metric is not the only decision-making tool available to the community. To facilitate decision-making within the ALS community a combination of metrics should be utilized, such as the Equivalent System Mass (ESM)-based ALS metric, but also those available through techniques such as life cycle costing and faithful consideration of the sensitivity of the assumed models and data. Often a lack of data is cited as the reason why these techniques are not considered for utilization. An existing database development effort within the ALS community, known as OPIS, may provide the opportunity to collect the necessary information to enable the proposed systems analyses. A review of these additional analysis techniques is provided, focusing on the data necessary to enable these. The discussion is concluded by proposing how the data may be utilized by analysts in the future.

Rodriquez, Luis F.↗
NASA NTRS2003

Risk-based decision making for novel technologies

ract summarizes a risk based decision-making process conceived of an developed at JPL and NASA, where it has been used to help plan and guide novel technology applications for use on spacecraft.

risk technology infusion↗
NASA NTRSDate not supplied

UAM Decision Making

NASA, in collaboration with the industry and FAA, is conducting research on Urban Air Mobility (UAM). UAM introduces unique and evolving operational characteristics unaccounted for within current transportation planning tools. This evolving modality requires a unique and comprehensive tool that integrates new and existing planning methodologies to provide a holistic solution for decision makers. NASA has identified a number of barriers and research areas related to aircraft, airspace, and communities as well as infrastructure requirements. The research will identify requirements related to urban capable aircraft and airspace technologies. While civil aviation authorities are responsible for safety and structure of operations through the air, the local and regional authorities are responsible for decisions related to location of vertiports, helipads, and airports. The implementation of UAM vertiports will consider diverse regional system categories such as weather, airspace restrictions, noise acceptability, surface traffic, availability of power, vertipad locations, routes, impact on surface traffic, safety and risks, economic impact, ingress/egress for electric/hybrid VTOL aircraft, applicable fire codes, evacuation strategy, zoning requirements, emergency preparedness, interactions with surface traffic, and community acceptance. Therefore, regional implementation bodies need a decision making tool to assess systemic dependencies in preparation for UAM impact on the region. We are developing a simulation and modeling tool that allows regional authorities to consider many factors while deciding the location of vertiport and UAM operations. The objective of this paper is to present the conceptual design of a comprehensive decision making tool to assist planning bodies in developing UAM infrastructure. Specifically, the UAM planning tool will simultaneously consider all relevant local/regional considerations to identify for vertiport locations and UAM operations for a region.

Parimal Kopardekar↗
NASA NTRS1992

Fuzzy sets, rough sets, and modeling evidence: Theory and Application. A Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection

The Dempster-Shafer theory of evidence is applied to a multiattribute decision making problem whereby the decision maker (DM) must compromise with available alternatives, none of which exactly satisfies his ideal. The decision mechanism is constrained by the uncertainty inherent in the determination of the relative importance of each attribute element and the classification of existing alternatives. The classification of alternatives is addressed through expert evaluation of the degree to which each element is contained in each available alternative. The relative importance of each attribute element is determined through pairwise comparisons of the elements by the decision maker and implementation of a ratio scale quantification method. Then the 'belief' and 'plausibility' that an alternative will satisfy the decision maker's ideal are calculated and combined to rank order the available alternatives. Application to the problem of selecting computer software is given.

Dekorvin, Andre↗
NASA NTRS2019

Onboard Decision-Making for Nominal and Contingency sUAS Flight

This study presents an onboard decision-making architecture for small unmanned aerial systems (sUAS). The decision-maker is part of NASA's SAFE50 project that is working under the UAS Traffic Management (UTM) Technical Capability Level (TCL) 4 to provide autonomous point-to-point UAV flight in BVLOS, high-density urban environments. The decision-maker monitors various metrics to determine the safety and feasibility of the mission and categorizes flight states as Nominal, Off-Nominal, Alternate Land, and Land Now in a finite state machine. Changes in the monitored metrics serve as transitions in the state machine and trigger replanning. Navigation degradation and communication failure are simulated to show the feasibility of the decision-maker framework in appropriately switching the flight state.

Baculi, Joshua↗
NASA NTRS1997

Automation Bias: Decision Making and Performance in High-Tech Cockpits

Automated aids and decision support tools are rapidly becoming indispensible tools in high-technology cockpits, and are assuming increasing control of "cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. This study was designed to investigate "automation bias," a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation "events," or opportunities for automation-related omission and commission errors. Pilots who perceived themselves as "accountable" for their performance and strategies of interaction with the automation were more likely to double-check automated functioning against other cues, and less likely to commit errors. Pilots were also likely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Mosier, Kathleen L.↗