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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRS1998

Development of a Search and Rescue Simulation to Study the Effects of Prolonged Isolation on Team Decision Making

The goals of this project were to identify and investigate aspects of team and individual decision-making and risk-taking behaviors hypothesized to be most affected by prolonged isolation. A key premise driving our research approach is that effects of stressors that impact individual and team cognitive processes in an isolated, confined, and hazardous environment will be projected onto the performance of a simulation task. To elicit and investigate these team behaviors we developed a search and rescue task concept as a scenario domain that would be relevant for isolated crews. We modified the Distributed Dynamic Decision-making (DDD) simulator, a platform that has been extensively used for empirical research in team processes and taskwork performance, to portray the features of a search and rescue scenario and present the task components incorporated into that scenario. The resulting software is called DD-Search and Rescue (Version 1.0). To support the use of the DDD-Search and Rescue simulator in isolated experiment settings, we wrote a player's manual for teaching team members to operate the simulator and play the scenario. We then developed a research design and experiment plan that would allow quantitative measures of individual and team decision making skills using the DDD-Search and Rescue simulator as the experiment platform. A description of these activities and the associated materials that were produced under this contract are contained in this report.

Entin, Elliot E.↗
NASA NTRS1992

Acquisition and production of skilled behavior in dynamic decision-making tasks

Currently, two main approaches exist for improving the human-machine interface component of a system in order to improve overall system performance - display enhancement and intelligent decision making. Discussed here are the characteristic issues of these two decision-making strategies. Differences in expert and novice decision making are described in order to help determine whether a particular strategy may be better for a particular type of user. Research is outlined to compare and contrast the two technologies, as well as to examine the interaction effects introduced by the different skill levels and the different methods for training operators.

Kirlik, Alex↗
NASA NTRS1994

Multi-objective decision-making under uncertainty: Fuzzy logic methods

Selecting the best option among alternatives is often a difficult process. This process becomes even more difficult when the evaluation criteria are vague or qualitative, and when the objectives vary in importance and scope. Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

Hardy, Terry L.↗
NASA NTRS2010

NASA Risk-Informed Decision Making Handbook

This handbook provides guidance for conducting risk-informed decision making in the context of NASA risk management (RM), with a focus on the types of direction-setting key decisions that are characteristic of the NASA program and project life cycles, and which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular decision problems that he or she faces. The handbook highlights major issues to consider when making decisions in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

Dezfuli, Homayoon↗
NASA NTRS2013

Test and Evaluation Metrics of Crew Decision-Making And Aircraft Attitude and Energy State Awareness

NASA has established a technical challenge, under the Aviation Safety Program, Vehicle Systems Safety Technologies project, to improve crew decision-making and response in complex situations. The specific objective of this challenge is to develop data and technologies which may increase a pilot's (crew's) ability to avoid, detect, and recover from adverse events that could otherwise result in accidents/incidents. Within this technical challenge, a cooperative industry-government research program has been established to develop innovative flight deck-based counter-measures that can improve the crew's ability to avoid, detect, mitigate, and recover from unsafe loss-of-aircraft state awareness - specifically, the loss of attitude awareness (i.e., Spatial Disorientation, SD) or the loss-of-energy state awareness (LESA). A critical component of this research is to develop specific and quantifiable metrics which identify decision-making and the decision-making influences during simulation and flight testing. This paper reviews existing metrics and methods for SD testing and criteria for establishing visual dominance. The development of Crew State Monitoring technologies - eye tracking and other psychophysiological - are also discussed as well as emerging new metrics for identifying channelized attention and excessive pilot workload, both of which have been shown to contribute to SD/LESA accidents or incidents.

Bailey, Randall E.↗
NASA NTRS1972

Interorganizational decision making.

The papers are both theoretical and applied. They include contributions from a spectrum of academic specializations and from practitioners representing several organizations. The papers are divided into theoretical and applied groupings reflecting a variety of systems levels and institutional examples, and into those papers which emphasized the organization structure requirements of interorganizational decision making, those that emphasized the behavioral requirements of interorganizational decision making, and those that developed decision technologies for interorganizational decision making.

Tuite, M.↗
NASA NTRS1992

Hurricane risk assessment to rollback or ride out a cost versus loss decision making approach

The potential exists that a hurricane striking the Kennedy Space Center while a Space Shuttle is on the pad. Winds in excess of 74.5 knots could cause the failure of the holddown bolts bringing about the catastrophic loss of the entire vehicle. Current plans call for the rollback of the shuttle when winds of that magnitude are forecast to strike the center. As this is costly, a new objective method for making rollback/rideout decisions based upon Bayesian Analysis and economic cost versus loss is presented.

Wohlman, Richard A.↗
NASA NTRS2004

Decision-Making in Flight with Different Convective Weather Information Sources: Preliminary Results

This paper reports preliminary and partial results of a flight experiment to address how General Aviation (GA) pilots use weather cues to make flight decisions. This research presents pilots with weather cue conditions typically available to GA pilots in visual meteorological conditions (VMC) and instrument meteorological conditions (IMC) today, as well as in IMC with a Graphical Weather Information System (GWIS). These preliminary data indicate that both VMC and GWIS-augmented IMC conditions result in better confidence, information sufficiency and perceived performance than the current IMC condition. For all these measures, the VMC and GWIS-augmented conditions seemed to provide similar pilot support. These preliminary results are interpreted for their implications on GWIS display design, training, and operational use guidelines. Final experimental results will compare these subjective data with objective data of situation awareness and decision quality.

Latorella, Kara A.↗
NASA NTRS1996

Planetary protection, legal ambiguity and the decision making process for Mars sample return

As scientists and mission planners develop planetary protection requirements for future Mars sample return missions, they must recognize the socio-political context in which decisions about the mission will be made and pay careful attention to public concerns about potential back contamination of Earth. To the extent that planetary protection questions are unresolved or unaddressed at the time of an actual mission, they offer convenient footholds for public challenges in both legal and decision making realms, over which NASA will have little direct control. In this paper, two particular non-scientific areas of special concern are discussed in detail: 1) legal issues and 2) the decision making process. Understanding these areas is critical for addressing legitimate public concerns as well as for fulfilling procedural requirements regardless whether sample return evokes public controversy. Legal issues with the potential to complicate future missions include: procedural review under National Environmental Policy Act (NEPA); uncertainty about institutional control and authority; conflicting regulations and overlapping jurisdictions; questions about international treaty obligations and large scale impacts; uncertanities about the nature of the organism; and constitutional and regulatory concerns about quarantine, public health and safety. In light of these important legal issues, it is critical that NASA consider the role and timing of public involvement in the decision making process as a way of anticipating problem areas and preparing for legitimate public questions and challenges to sample return missions.

NASA Discipline Number 59-10↗
NASA NTRSDate not supplied

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗
NASA NTRS1991

Expert decision-making strategies

A recognition-primed decisions (RPD) model is employed as a framework to investigate crew decision-making processes. The quality of information transfer, a critical component of the team RPD model and an indicator of the team's 'collective consciouness', is measured and analyzed with repect to crew performance. As indicated by the RPD model, timing and patterns of information search transfer were expected to reflect extensive and continual situation assessment, and serial evaluation of alternative states of the world or decision response options.

Mosier, Kathleen L.↗
NASA NTRS2013

Understanding Crew Decision-Making in the Presence of Complexity: A Flight Simulation Experiment

Crew decision making and response have long been leading causal and contributing factors associated with aircraft accidents. Further, it is anticipated that future aircraft and operational environments will increase exposure to risks related to these factors if proactive steps are not taken to account for ever-increasing complexity. A flight simulation study was designed to collect data to help in understanding how complexity can, or may, be manifest. More specifically, an experimental apparatus was constructed that allowed for manipulation of information complexity and uncertainty, while also manipulating operational complexity and uncertainty. Through these manipulations, and the aid of experienced airline pilots, several issues have been discovered, related most prominently to the influence of information content, quality, and management. Flight crews were immersed in an environment that included new operational complexities suggested for the future air transportation system as well as new technological complexities (e.g. electronic flight bags, expanded data link services, synthetic and enhanced vision systems, and interval management automation). In addition, a set of off-nominal situations were emulated. These included, for example, adverse weather conditions, traffic deviations, equipment failures, poor data quality, communication errors, and unexpected clearances, or changes to flight plans. Each situation was based on one or more reference events from past accidents or incidents, or on a similar case that had been used in previous developmental tests or studies. Over the course of the study, 10 twopilot airline crews participated, completing over 230 flights. Each flight consisted of an approach beginning at 10,000 ft. Based on the recorded data and pilot and research observations, preliminary results are presented regarding decision-making issues in the presence of the operational and technological complexities encountered during the flights.

Young, Steven D.↗
NASA NTRS2012

Using M and S to Improve Human Decision Making and Achieve Effective Problem Solving in an International Environment

In the international arena, decision makers are often swayed away from fact-based analysis by their own individual cultural and political bias. Modeling and Simulation-based training can raise awareness of individual predisposition and improve the quality of decision making by focusing solely on fact vice perception. This improved decision making methodology will support the multinational collaborative efforts of military and civilian leaders to solve challenges more effectively. The intent of this experimental research is to create a framework that allows decision makers to "come to the table" with the latest and most significant facts necessary to determine an appropriate solution for any given contingency.

Christie, Vanessa L.↗
NASA NTRSDate not supplied

MAGE: Alleviating Uncertainty in Real-Time Decision-Making as a Function of Problem Complexity

In this paper, we discuss a critical aspect of uncertainty in the operation of complex systems, such as the future air traffic: the ability of agents in the system to arrive at satisfactory decisions and the attendant actions as a function of problem complexity. Intuitively, when the problem complexity is manageable, given an appropriate decision problem formulation and solution tools, an agent (computational or human) has no trouble arriving at a solution that yields good outcomes for the agent and the system. Growing problem complexity results in progressively larger computational problems that may yield suboptimal solutions or even be intractable within required time limits or at all. We propose a measurable representation of complexity in terms of problem tractability and quality of solutions. We also propose a computational scheme, MAGE (Monitor, Anticipate, Guide, Evolve), for detecting approaching transitions from efficient decision-making states to inefficient to unsafe ones, so that operations based on decision-making can be reconfigured to forestall unfavorable transitions, returning to efficient modes when complexity diminishes. Maintaining tractable complexity reduces the uncertainty in the outcomes of decision-making. We describe the general scheme, an outline of MAGE applied to managing airspace complexity, and initial examples of investigating the tractability of problem-solving schemes.

complexity management↗