Jason Fox

Analogical and case-based reasoning for predicting satellite task schedulability

Satellites represent scarce resources that must be carefully scheduled to maximize their value to service consumers. Near-optimal satellite task scheduling is so computationally difficult that it typically takes several hours to schedule one days activities for a set of satellites and tasks. Thus, often a requestor will not know if a task will be scheduled until it is too late to accommodate scheduling failures. This paper presents our experiences creating a fast Analogical Reasoning (AR) system and an even faster Case-Based Reasoner (CBR) that can predict, in less than a millisecond, whether a hypothetical task will be scheduled successfully. Requestors can use the system to refine tasks for maximum schedulability. We report on three increasingly narrow approaches that use domain knowledge to constrain the problem space. We show results that indicate the method can achieve >80% accuracy on the given problem.

Multimodal interaction techniques for situational awareness and command of robotic combat entities

In the next generation of Army combat vehicles, the future combat system (FCS), lightly-armored robotic vehicles are commanded by human commanders operating from within moving command vehicles, and well back from the forward edge of the battle area. Two key questions to be answered for the successful realization of FCS are how can the commander maintain situational awareness and what methods best allow the commander to interact with these robotic forces to achieve the mission goals. In our research, our approach is to immerse the commander in a virtual battlespace, with capability to directly interact with visual representations of the robotic entities. We developed a multimodal (visual, speech, and gesture) interaction method and specific techniques that allow the commander to navigate the virtual battlespace and command robotic entities while seated in a vehicle and without use of a keyboard.

Evaluating Visualization Modes for Closely-Spaced Parallel Approaches

Raytheons TACEC (Terminal Area Capacity Enhancement Concept) proposes to increase airspace capacity by using closely-spaced formations of arriving and departing aircraft to greatly increase airport capacities. However, a blunder in a tightly-spaced formation could cause a collision with another aircraft or its wake vortices. Therefore, humans need tools and visualization aids to detect and respond to blunders. This paper is the first in a series of experiments to evaluate the ability of different visualization modes to enable detection of lateral blunders. We tested four viewpoints, one warning aid, and three blunder speeds in a within-subjects design. This study had twelve participants. The main result was that changing the viewpoint made a large difference; the cockpit view was by far the worst. Blunder detection varied by speed and was difficult in the presence of noise. Future experiments should use more realistic simulators and pilots as participants.

Visualization Concepts for Generating Insight from NAS Simulation Data

¶This paper describes our initial steps to develop new visualization concepts that can generate insight and understanding from National Airspace System (NAS) simulation data. The capacity of the United States’ National Airspace System (NAS) must at least double to handle the projected increase in passenger demand by 2025. To address this challenge, new capacity-enhancing concepts are being developed. These concepts are tested and evaluated on a NAS simulation tool called the Airspace Concept Evaluation System (ACES). Concept developers need improved visualization techniques to better understand ACES simulation outputs, and thereby comprehend the strengths, weaknesses and effects of their capacityincreasing concepts. Examining ACES outputs is a nontrivial task. ACES simulates the entire NAS and generates an enormous amount of data. A single simulation run can include over 60,000 flight segments and output tens of gigabytes of data. Traditional approaches for displaying these outputs fall short of what concept developers need. Existing visualization techniques are straightforward geographic plots of aircraft or their related metrics (density, environmental impact, delay, etc.), which are often overwhelming and not illuminating. For example, drawing 10,000 aircraft at their true locations over the continental United States results in a density that is too high for observers to understand the situation and extract useful information. The contribution of this paper is in describing new visualization concepts for this problem domain, where our visualizations do not rely primarily upon plotting data at their true geographic coordinates. We draw from cognitive science principles, perception, ATM characteristics and information visualization techniques to synthesize new approaches for displaying ACES data. Our goal is to enable the user to detect subtle correlations, patterns, trends and relationships that provide insight. We describe our general strategies and approaches, including the results of asking concept developers what specific questions they wanted a visualization tool to answer. Then we present eight new visualization concepts that reveal different aspects of the NAS simulation data, with preliminary implementations of three concepts. Future work includes evaluation on more datasets. A measure of success will be the ability of these new visualization modes to enable users to see subtle but important patterns, trends, correlations, features, and relationships that they could not previously see by any previous means. The goal is to generate insight and allow observers to find important characteristics that they did not even know to look for initially.