| 2006 Technology
Symposium > Decision Support
Decision Support
This area focuses on cognitive-centered decision support applications
and new methods and tools for developing effective systems that support
decision-making. Emphasis is placed on decision-making in dynamically
changing real-time environments (occurring in a day or less). Research
in human decision-making to enable the development of better support systems
for the military or other sponsors is covered in this area. Also covered
is the demonstration of decision aids that advance the state of the art.
Advanced ADS-B Applications
Anand Mundra, Principal Investigator
Location(s): Washington
Problem
Introducing technologies into the NAS is a long process that must show continuing benefit to the stakeholders. Future applications of Automatic Dependent Surveillance-Broadcast (ADS-B) are needed to encourage equipage and to provide future benefits. No one is looking at the next "wave" of applications.
Objectives
This project will identify the major promises and the "tall poles" in implementing ADS-B applications, and demonstrate at least one of them in a laboratory environment. In the course of this research, stakeholders will be involved to provide feedback and to form the basis for acceptance of the applications.
Activities
A controller task analysis, along with the knowledge of existing applications, will lead to the identification of potential concepts. The benefits and development risks of these concepts will be estimated. The concepts will be mocked up via selected visualization techniques. With feedback from the stakeholders, a set of core applications will be identified and a lab demonstration will be developed.
Impact
New ADS-B applications will lead to improved controller productivity. The research itself will focus the stakeholders on the issues and jump start the implementation of these applications. MITRE and the FAA will maintain leadership in the worldwide effort to introduce ADS-B.
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Advanced Soldier Sensor Information System Technology (ASSIST)
Lisa Harper, Principal Investigator
Location(s): Washington
Problem
Warfighters are called upon to report key observations and experiences during ground missions quickly and accurately. The confusion of the battlefield, combined with the physical and psychological stresses, can make this task very difficult. Furthermore, today's verbal and text-based reports limit the extent of information that is conveyed and critical information is therefore lost.
Objectives
The objective of the program is to exploit soldier-worn sensors to augment soldiers' recall and reporting capability and thereby enhance situational understanding. The effort will develop information processing and representation tools to maximize the utility of data collected by the multimodal sensors.
Activities
MITRE will assist this program in three ways. First, we will aid in developing a systems integration plan as a means for surveying the problem scope. Second, we will assess user requirements by targeting potential military user groups and scenarios. Third, we will assist with baseline evaluations of a field-deployable capture system and back-end retrieval and visualization tool.
Impact
This work will ensure that DARPA objectives are compatible with DoD operational needs while taking into account physical and cognitive needs of individual combatants equipped with ASSIST devices.
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Advanced TFM Visualization and Interactions
Mark Huberdeau, Principal Investigator
Location(s): Washington
Problem
Today's traffic flow managers use fragmented capabilities when identifying, evaluating, and communicating potential constraints that limit traffic flow. The information necessary for decision making is not integrated and is not consistent among Traffic Management Units, resulting in limited situational awareness across the NAS. Poor data integration, limited situational awareness, and a difficult collaboration process typically result in inefficient system operations.
Objectives
This project will explore new technologies such as nonlinear visualization, 3D imagery, virtual team rooms, and symbiotic display partnerships to improve the comprehension, situation awareness, and performance of traffic managers. The objective is to integrate large amounts of information used for decision support and status monitoring over multiple and shared stakeholder environments.
Activities
We will research other domains that use advanced technologies for data integration and collaboration (e.g., commercial gaming) and investigate their applicability to TFM. We will then find and brainstorm with subject matter experts to identify opportunities to capitalize on new techniques for problem solving. We will identify TFM needs through storyboarding and scenario development.
Impact
This project has the potential to change the way TFM is conducted by developing a framework of collaborative decision support and simulation technologies. A more strategic approach to identifying the issues and developing solutions will be possible given that the same data and tools will be available to traffic flow managers across the NAS.
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Advanced Visual Filtering of Dynamic Data
Erika Darling, Principal Investigator
Location(s): Washington and Bedford
Problem
Warfighters and other situationally-oriented information consumers constantly face situations that require them to immediately find and mentally fuse essential information within a large information space. This poses a challenge for warfighters who work with static data and an even more pressing concern for warfighters who must synthesize dynamic data, such as locations of sensor assets or weather patterns.
Objectives
This effort will investigate effective visual strategies for filtering dynamic data. Applying lensing concepts to dynamic data will facilitate understanding of the strategies' effectiveness in aiding decision making in continuously changing environments.
Activities
By characterizing our sponsors' needs in terms of decluttering dynamic datasets, we will produce a taxonomy to map dynamic data types to the corresponding filtering strategies. We will use this taxonomy to develop a prototype of visualization techniques for filtering dynamic data, with specific emphasis on lensing strategies. Experimentation with these techniques will determine their effectiveness.
Impact
Warfighters in domains that include mission planning, weather forecasting, and intelligence integration must make sense of vast amounts of dynamic data to act. However, they have been neglected in the information visualization field. This effort will advance understanding of effective filtering strategies for dynamic data to promote faster and better-informed decision making.
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Agile Missile Event Reporting
Alberto Andrade, Principal Investigator
Location(s): Washington and Bedford
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Air Traffic Planning in an Uncertain World
Craig Wanke, Principal Investigator
Location(s): Washington
Problem
Airspace congestion management decisions are based on imperfect predictions of demand and capacity; however, prediction uncertainty is not explicitly factored into the decision-making process. Thus, solutions are large scale and conservative, inducing excess delay and workload.
Objectives
Our objective is to factor uncertainty into decision making by (1) quantifying it, (2) developing and prototyping algorithms to solve congestion, and (3) demonstrating the benefits of the approach for typical congestion problems.
Activities
First, drawing on the uncertainty models and initial problem solution models developed in FY05, we will build a prototype that can solve operational-scale congestion problems using individual aircraft reroutes and ground delays. Second, we will develop an estimate of the potential benefits of this concept and system.
Impact
Probabilistic congestion management has the potential to greatly improve the efficiency of air traffic flows, especially when those flows are faced with disruptive weather conditions. This project provides the analytical basis for a future probabilistic congestion management system, as outlined in plans developed by the FAA and the Joint Project Development Office (FAA, NASA, and industry participants).
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Applying User Models to Improve Team Decision Making
Brad Goodman, Principal Investigator
Location(s): Washington and Bedford
Problem
People who do not always work together must sometimes meet to solve important and possibly time-critical problems. MITRE's sponsors are rapidly accepting computer-supported collaborative work environments as a medium to bring people together to discuss such problems. The participants share information, insight, and advice. The team decision-making structure afforded by collaborative environments, however, does not necessarily encourage productive participation.
Objectives
This project will develop models of users of collaborative environments to promote common situation awareness and understanding that can lead to successful collaborative decision making. The user models help monitor the quality of group interaction in pursuit of a solution to a mutual problem. These user models move with users and persist from session to session and group to group.
Activities
We will develop an intelligent steward agent to guide team members through collaborative decision making. We will analyze meeting corpora from the research community to determine characteristics of decision-making dialogues, and will conduct controlled studies to evaluate collaborative activities and highlight collaborative behavior. We will track topics and stages of decision making and formulate user models as meetings proceed.
Impact
Many MITRE sponsors use collaborative technology to bring experts together to make decisions. The development of criteria to help in the selection of team members and of techniques to guide teams towards consensus can lead to more cohesive teams, improved decisions, and enhanced knowledge sharing. The proposed research will provide a more effective foundation for sharing expertise in collaborative environments.
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Assessment of 4D Applications for Future NAS Operations
Greg Nelson, Principal Investigator
Location(s): Washington
Problem
Many future concepts for the National Airspace System (NAS) incorporate the use of time, in addition to the traditional longitude, latitude, and altitude dimensions. What are the specific NAS applications, such as separation assurance, landing, or congestion management, where the use of 4D trajectories provides an advantage?
Objectives
The objective is to establish an analytic framework around the 4D trajectory concept using "simple models." We intend to explore issues surrounding control tolerances, bounds of uncertainty, and initial benefit estimates for 4D applications.
Activities
We will identify how NAS applications would implement 4D concepts. We will then develop simple models to model key inputs and basic algorithms, and perform sensitivity analysis. Finally, we will quantify the initial benefits associated with 4D trajectories for each NAS application.
Impact
This research will help to identify what role 4D trajectories can realistically provide in the future NAS, and begin identifying the most appropriate transition areas that could use a time-based component.
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Collaborative Data Objects
Dan Winkowski, Principal Investigator
Location(s): Washington and Bedford
Problem
The utility of enterprise chat tools has led to their increased use for C2 decision making. However, poor integration with "systems of records" hinders the seamless flow of decision-quality information. Also, for data-intensive collaboration these tools can actually present obstacles to information sharing, shared situational awareness, and self-synchronization. Issues of ambiguity, accuracy, and quality are prevalent.
Objectives
Collaborative data objects (CDOs) are a proposed methodology to introduce structured data to unstructured conversational chat sessions without disrupting the proven lightweight style of collaboration on which warfighters depend.
Activities
We will develop a CDO description language as well as a framework to host, manage, and synchronize CDOs across chat sessions. Standards will be defined for accessing mission application and enterprise service functionality through CDOs and to facilitate seamless information flow into and out of chat sessions. A scenario and set of initial CDOs will be developed to support assessment.
Impact
Our vision is a collaborative environment rich in data objects that enable improved application data exchanges, interaction with agents via a rich semantic foundation, interaction with other collaborative media (maps, shared applications), and exploitation (searching, cataloging, learning) of saved conversational threads based on CDO markers. Technology transfer will take place through interactions with various standards bodies.
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Estimating Controller Productivity in the Future NAS
Dan Kirk, Principal Investigator
Location(s): Washington
Problem
To accommodate projected traffic volume and complexity, and to contain the cost of providing air traffic management services, fundamental shifts in operational roles and responsibilities will be required throughout the NAS. Improved tools and techniques are needed to estimate controller productivity as a result of these changes and to aid future workforce planning and the prioritization of supporting automation enhancements.
Objectives
We seek to develop improved tools and techniques to estimate controller productivity, with a focus on creating a model for extension of human-in-the-loop experimental results to an NAS-wide basis. This model will be readily tunable as new results are obtained and NAS enhancements and traffic forecasts are refined.
Activities
Our approach will proceed in an iterative manner, starting with the application of existing controller task time models and task frequencies as measured in NAS-wide recordings. This model will be successively refined based on results from ongoing laboratory experimentation with automation enhancements. Additional studies will address the relationships among workload, controller productivity, and staffing needs to support future workforce planning.
Impact
This work will help to establish the link between technology changes and controller productivity, an understanding that is essential for future workforce decisions and for the prioritization of automation enhancements.
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Explanation-Based Decision Making
Brant Cheikes, Principal Investigator
Location(s): Washington and Bedford
Problem
Research in human judgment and decision-making shows that novices and domain experts alike make a variety of predictable mistakes in forming assessments, estimates, and predictions. Failures in judgment can be enormously costly in both wealth and lives. Yet systematic methods to help minimize such failures or reduce their impact are few, and are inconsistently taught or applied across the government.
Objectives
This project will evaluate a new framework for the design of cognitive support tools, based on the claim that explanations are central to how people reason and decide. Driving this research is a vision of the role and purpose of cognitive support tools for analytic judgment, namely, that such tools should enable analysts to create external representations of decision problems.
Activities
We will develop a prototype and conduct both formative and controlled experiments to evaluate explanation-based decision making (EBDM) as a guiding theory for cognitive support tools. We will implement EBDM principles in a software application to support the cognitive analytic processes of marshaling evidence and exploring hypotheses. We will conduct experiments to measure improvements in hypothesis-testing behavior.
Impact
This research will deepen MITRE's understanding of the core cognitive processes that drive decision making, and enable us to articulate technical requirements for cognitive support tools for analysis and decision making. This work will position us to advise the government knowledgeably on current and future technology investments in this area.
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Facilitating Sense-Making for Situational Awareness
Christopher Berube, Principal Investigator
Location(s): Washington and Bedford
Problem
Military domains that use Internet chat to supplement their situational awareness (SA) do not currently exploit the correlation between chat and structured data (e.g., ground moving target indicator (GMTI) reports). Therefore, those who rely heavily on chat for sense-making are forced to establish relationships manually (if they do so at all) between chat and structured data, often under time pressure.
Objectives
Our research will focus on the development of algorithms and a software prototype for the correlation of data in multiple chat rooms with data from structured sources. Such sources will include those typically exploited in time-critical targeting (TCT) domains, such as GMTI and intelligence platforms. Algorithms for aggregating data will be developed to support correlation with chat and high-level SA.
Activities
We will optimize existing information extraction software for use with chat drawing on lexicons developed for TCT domains. Development of software for extracting elements from structured data will support the correlation of these elements with chat using algorithms based on statistical metrics and heuristics. We will use real and simulated data sets to demonstrate a prototype system, including user interfaces.
Impact
This research will allow users to establish relationships between disparate data sources, resulting in a better capability to balance the demands of monitoring data across multiple chat rooms while exploiting "traditional" structured data sources. While this prototype is being developed using selected sources from a TCT environment, other sources of structured data (e.g., air tasking orders) can be considered.
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Improving Human/UAV Interaction for Intelligence, Surveillance, and Reconnaissance
Jill Drury, Principal Investigator
Location(s): Washington and Bedford
Problem
Due to the increasing importance of UAV operations and the ramp-up of the Distributed Common Ground System (DCGS), we urgently need to support efficient and flexible UAV operations. UAV operations are currently manpower intensive and confined to a single location. Moreover, they are often non-intuitive and plagued by "mishaps."
Objectives
Our research will determine ways to provide better situation awareness (SA) of both UAV team members' activities and the ISR environment and identify opportunities for generalizing our understanding of improved SA to other C2 domains. We will provide guidance for whether/how UAV teams could be distributed, and develop and evaluate interaction designs that support small teams operating multiple UAVs simultaneously.
Activities
Our technical approach combines observation, interviews, analysis, prototyping, and experimental techniques. We will study both live and simulated UAV operations with both large and small UAV platforms. Our analysis results will inform new interaction designs that will be validated via experimentation. We are partnering with Dr. Michael Goodrich of Brigham Young University, a recognized expert in human-UAV interaction.
Impact
This work will result in UAV interaction that better facilitates SA acquisition and team coordination, a smaller number of operators placed in harms' way, input into the debate about distributed UAV operations, and fewer UAVs lost to mishaps. A broader impact could arise from insights into providing better SA for domains beyond UAV operations.
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Integrating Judgment and Technical Data Analysis
Paul Lehner, Principal Investigator
Location(s): Washington and Bedford
Problem
When applied in the real world, technical analysis and interpretation of sensor data involve considerable subjective judgment. Unfortunately, both research in psychology and experience tell us that expert judgments of this type are consistently subject to well-known biases and errors.
Objectives
This project will develop and test a structured analytic method, called Causal Judgment Analysis (CJA), to support judgment in technical data analysis.
Activities
CJA was initially developed to support counter deception analysis. On this project, CJA will be adapted to problems in technical data analysis. We will test the method by examining its performance on problems where ground truth is known and by assessing its impact on analytic thought on difficult current analysis problems.
Impact
If successful, this project will provide a rigorous analytic method for stepping through difficult technical analysis problems. This will lead to more accurate interpretation of sensor returns and to better understanding of the subjective judgments on which the interpretation depends.
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Mental Models in Naturalistic Decision Making
Kevin Burns, Principal Investigator
Location(s): Washington and Bedford
Problem
Systems engineering efforts are often based on informal and inadequate models of how, psychologically speaking, people make decisions and what, computationally speaking, people need to make better decisions. MITRE and its sponsors need computational models of cognitive processes in order to advance the design of information systems in command and control applications.
Objectives
This research will develop computational models of the cognitive processes that underlie human decision making in prototypical tasks of command and control. The computational models will employ a "bounded Bayesian" theory that treats human decision makers as rational (Bayesian) but limited (bounded) by natural constraints.
Activities
The research methods will include human experiments and agent simulations in test beds that pose cognitive challenges like those of strategic command and control. One test bed is a suite of "Pared-down Poker" games that has been designed for web-based experiments on "inferences" (under uncertainty) and "investments" (dynamic decisions). Another test bed, in collaborative research with MIT's Human and Automation Lab (HAL), is being used to study decision support for the specific C2 problem of dynamically scheduling UAVs.
Impact
The research products will be computational models of human decision making and conceptual systems for automating and improving human decision making. These models and systems will be assessed in laboratory test beds in order to establish a basis for improving C2 in the field.
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Perceptive Assistive Agents in Team Spaces
Lisa Harper, Principal Investigator
Location(s): Washington
Problem
The use of next generation interface technologies to facilitate human-human collaboration and human-computer interaction has tremendous potential for enhancing team interaction. However, new devices and technologies cannot be inserted successfully unless they are adapted to the dynamics of the group's structure and interactions. Furthermore, the insertion of any particular technology may have unanticipated and unintended consequences. We have designed an Experimental Team Room (ETR) that is a replica of MITRE's standard conferencing environment. However, this facility has been modified to observe and record user interactions with room devices and research products.
Objectives
We focus on the ability of assistive agents to monitor, access, and manipulate elements of the physical context. Our hypothesis is that we can enhance the interactions of teams and performance in both local and remote groups by using perceptive personal agents and team space agents that mediate interactions between humans and the collaboration environment.
Activities
We are leveraging the ETR to develop a sensor-based environment and a virtual human (Emma) that can access, monitor and change the physical environment. Users can communicate with Emma, the Electronic MITRE Meeting Assistant, in a variety of ways such as speech, gesture or via a graphical interface. We are endowing Emma with the ability to recognize individuals via speech and face recognition as well as the ability to track their location in space. We believe that a perceptive agent that is more aware of the physical context of a meeting will be more flexible and responsive to user needs than current meeting room interfaces.
Impact
By leveraging our own operational mission and corporate expertise, we have a tremendous opportunity to study real user populations over an extended period of time in such a way to inform usability issues critical to related C3I environments and to Section 508 of the Rehabilitation Act.
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Sense and Avoid for Small Unmanned Aircraft
David Maroney, Principal Investigator
Location(s): Washington and Bedford
Problem
This research will address the question "Can small autonomous aircraft reliably detect and avoid collision (by reacting predictably) with objects in their path, both stationary and moving, that do not announce their position?" Many research efforts focus on one component of this "detect/sense/avoid" question, but the combination has not been broadly addressed.
Objectives
The project will investigate obstacle-sensing technologies, as well as avoidance methods and algorithms, to assemble unique combinations for comprehensively addressing the research question. Through a progressive set of laboratory and field tests, we hope to prepare initial sense-and-avoid airborne flight demonstrations by the end of the first year of research.
Activities
We will conduct this research through a multi-pronged approach, to include investigating new sensor systems and combinations, examining and extending detection and avoidance algorithms, developing system designs and documenting trial results (both in the lab and in the field), exploring FAA constraints on unmanned aerial system (UAS) flights, and recommending new FAA and military procedures.
Impact
Direct impacts of this research include improving the collision avoidance capabilities of small UASs, while having them act predictably in civil/military encounters; improving survival of UASs and unintentional targets; and informing policy decisions on certification and regulation. Additionally, this research helps to support corporate goals of broad cross-center involvement in UAS research.
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Sensor PLanning and Analysis Tools (SPLAT)
Kevin Kelly, Principal Investigator
Location(s): Washington and Bedford
Problem
The U.S. Army is deploying a multitude of ISR assets to provide information superiority at the tactical level. Achieving this goal depends on effective planning and use of the assets in ways that best meet the information needs of tactical missions. ISR planning requires consideration of many factors, often outside the core expertise of day-to-day tactical staff officers.
Objectives
Specific objectives include improving the quality of sensor plans, simplifying development of sensor plans, and developing a net-centric distributed framework for sensor management. The SPLAT project will also provide a suite of decision support tools that support an Army Brigade Combat Team in their initial development, monitoring, and dynamic replanning of sensor plans.
Activities
We will develop a software architecture for distributed ISR management that will detail functional components, internal and external interfaces, and how the SPLAT components would be instantiated on existing/emerging ISR/C2 systems. We will first focus on providing a baseline suite of decision support tools to support the initial development of the ISR plan. Experimentation and analysis will be conducted to evaluate the SPLAT efforts.
Impact
This project will develop software prototypes that could provide insights and technical approaches applicable to the Distributed Common Ground Station-Army program. Future Army combat forces will need automation to plan and manage an unprecedented suite of ISR resources effectively; the knowledge and techniques developed in this project may also be applicable to this future combat environment.
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Separation Standards Analysis
Bill Swedish, Principal Investigator
Location(s): Washington
Problem
New technologies and operational concepts offer opportunities to reduce current separations between aircraft and increase the capacity of the NAS, however, the appropriate level of safety must be maintained. Current separation standards are based on different rationales and safety analysis methodologies and thus provide incomplete guidance at best for evaluating new standards.
Objectives
This project will propose an analytical framework for evaluating separation standards. The framework will provide a consistent level of safety by incorporating the principles of the FAA Safety Management System. This framework will also be flexible and expansive enough to accommodate new technologies (such as Automatic Dependent Surveillance-Broadcast), new operations (such as UAVs), and new operational concepts (such as self-separation).
Activities
After reviewing the rationale behind current separation standards (to the extent it is documented), we will identify the basic safety principles involved. We will develop a framework for evaluating new separation standards that reflects best current practices adapted to the aviation environment. This proposed framework will be tested by applying it to one or more future scenarios.
Impact
A successful framework would allow the maximum operational benefit to be obtained from new technologies and concepts by giving confidence that the appropriate level of safety has been maintained. Identifying and addressing potential risk areas early will reduce overall programmatic risk and cost.
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UAS Conflict Detection and Collision Avoidance in Civil Airspace
Andrew Zeitlin, Principal Investigator
Location(s): Washington and Bedford
Problem
Unmanned vehicles pose new issues in safely operating within the NAS. Their maneuverability, mission types, and operational response differ from those of conventional aircraft. Traffic Alert and Collision Avoidance System (TCAS) and conflict probe technologies were not designed for these uses and may be inadequate to reduce collision risk. The safety of conventional aircraft from unmanned aerial systems (UASs) must be addressed.
Objectives
This project will develop requirements for safely detecting conflicts and avoiding collisions for UASs whose remote piloting introduces delay and whose maneuver performance is greatly constrained. It will also demonstrate a concept offering safety and independence of functions comparable to those of civil aircraft, with operational compatibility between those functions, and will bound the maneuver performance needed to provide appropriate safety levels.
Activities
We will perform analysis and fast-time simulation to test standard and modified TCAS for UAS maneuvers and delays. We will test and demonstrate User Request Evaluation Tool (URET) conflict detection for UAS parameters and unique missions in MITRE's Air Traffic Management laboratory. We will also prototype remote pilot displays that concentrate on conflict and collision functions.
Impact
The aviation industry and the DoD are actively seeking UAS access to the NAS. The FAA requires that safety in U.S. airspace be conclusively demonstrated. By demonstrating to stakeholders how safety can be proven with realistic requirements, this project hopes to facilitate airspace access for UASs.
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Visualization for Improved Situational Awareness
Peter Firey, Principal Investigator
Location(s): Washington and Bedford
Problem
Transformational warfighting systems under development rely heavily on "enhanced situational awareness (SA)" to understand better than the opponent, focus effects, and avoid harm. How can warfighters know when they have SA, where they have it, and whether they have enough? How do they effectively share their SA and insights to contribute to a force wide SA?
Objectives
We will integrate SA Overlay (SAO), simulation delivery, data mining, and statistical analysis tools and concepts into a comprehensive approach for battlespace understanding. We will work with sponsor warfighters and developers to support a rapid spiral pattern of research and development of truly useful SA visualization tools and then rapidly provide operationally useful SA visualization services to deployed warfighters.
Activities
We will design and prototype a VISA experimental environment that integrates SAO and other SA visualization components into a networked environment that fits into existing and planned DOD C2 environments. We will try out the VISA ideas on representative warfighters and obtain feedback to improve the prototypes. We hope to conduct two spirals of prototype development, each followed by a user-supported experiment.
Impact
The VISA technologies "at a glance." VISA should also enable commanders to convey their desires for SA generation and maintenance and allow ISR operators to better plan information collection for SA.
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