Active Projects

(Project description of active projects is provided below. Graduate student managing the project is given in the bracket).

  1. Identifying cognitive control modes from operator control data (Denys);
  2. Effect of control authority on system acceptance;
  3. Abductive logic as a human decision-making approach;
  4. Physiological monitoring using nano-sensors (Denys);
  5. Intensity as a safety measure;
  6. Level IV situation awareness;
  7. Control theoretic models of complex human-integrated systems;
  8. Detecting human machine interaction problems in continuous control data (Audrey);
  9. Improving infusion pump alerting system performance (Jeongjoon);
  10. Identifying nurses’ mental models of infusion pump alerting systems;
  11. Mitigating disruptions using dynamic interacting networks;
  12. Using distributed scheduling for ground traffic problems (Daniel);
  13. Graph-theoretic task analysis (Harsh); and
  14. Emergent behavior from graphs of sentence diagrams

 Project Descriptions

  1. In this project, we are attempting to determine whether cognitive control modes, as specified by Hollnagel, are identifiable from operator control data, such as system state data, operator inputs, or operator physiological data.  Experience with experiment design and statistics is helpful but not required.
  2. In this project, we want to test the hypothesis that operators will accept a higher system error/accident rate if they believe that they have control over whether an error or accident occurs, compared to the situation where they cannot control errors/accidents. Experience with experiment design and statistics is helpful but not required.
  3. We believe that humans use “abductive logic” as a general strategy for decision-making, and that its use is compulsive.  In this project, we would test that belief, which implies that, if true, one could manipulate people’s decisions by changing the person’s expectations. Experience with decision making, experiment design, and statistics is helpful but not required.
  4. In this project we are evaluating whether existing self-powered nano-sensors can be used to identify changes in workload, stress, and/or cognitive control mode. Experience in signal analysis and statistics is helpful but not required.
  5. We have developed a new measure of safety, called “intensity,” that identifies potentially hazardous situations as opposed to predicted hazardous situations.  In this work the measure’s characteristics in various systems will be investigated, and its presentation will be developed.  Experience in data analysis and visualization is helpful but not required.
  6. The concept of “intensity” can be considered a new level of “situation awareness” over and above Endsley’s three-level model.  This project will define level IV situation awareness and test it. Experience with the concept of situation awareness is helpful; good writing and presentation skills are highly desired.
  7. In this highly exploratory work, complex human-integrated systems are modeled using control theory notation.  Those models are used to create symbolic definitions of systems, system-of-systems, and human-integrated systems.  Knowledge of control theory is required.
  8. In this work, data analysis/data mining methods are used to attempt to identify specific human-machine interaction issues within the type of continuous or discrete system data normally recorded.  Statistics and data mining skills are highly desired.
  9. In this work, a decision support system’s effect on the false alarm rate of an infusion pump system is evaluated.  Database and statistics knowledge is helpful but not required.
  10. This project will utilize a survey method to try to identify the mental models of nurses who interact with infusion pump systems.
  11. Air traffic operations can be viewed as a set of dynamic interacting networks.  In this view, disruptions are caused by mismatches in the interactions of these dynamic networks.  This project will create the framework for considering these problems in this way, and identify whether network characteristics correspond with good and bad disruption recovery.
  12. A loosely-coupled scheduling algorithm was developed for air traffic.  In this project, the algorithm is applied to ground traffic and its effect investigated.
  13. Tasks can be viewed as a graph of simple interactions, where the nodes are the simple interactions and the links between the nodes are the probability of that transition occurring.  In this work we evaluate whether this approach to task analysis provides useful measures and insights.
  14. Given a large set of textual input data, one could construct a system to diagram the sentences in the text and create a graph of the connections between terms.  Given particular output goals, that system may be capable of emergent behavior where it achieves its goal in human-like ways.  This project will develop such a system and evaluate its performance/behavior.

Past Projects

  • Development of Hybrid Modeling Methods to Detect Flight Deck Human-Automation Issues (NASA funded, Quang Dao, spring 2017)
  • Artificial Horizon Design Study (Ding Ding, fall 2016)
  • Wearable Device Data Analytics (Jocelyn Dunn, fall 2016)
  • Grissom Accessibility Project (Audrey Reinert, fall 2016)
  • Evaluating the performance of humans or organizations using learning curves. Simulation with Arena/Vatsim
  • A study of human factors and its application in system design process
  • Air Traffic Control Measures
  • An Architecture Study for a Future Safe, High-Capacity Air Transportation System
  • Website Redesign: User Experience and Interaction Design
  • Arduino At Home: In-home automation with arduino
  • Infusion Pump Mental Model for healthcare providers