Previous research indicates that expert air traffic controllers utilize specific strategies when scanning en-route radar displays for detecting loss of separation between aircraft. These strategies can be categorized into four main types based on their geometric pattern: circular, spiral, linear, and quadrant-based strategies. Most of the experts in the research stated that they primarily use the circular strategy throughout their tasks. To investigate whether these findings can be applied to non-experts as well, an application was developed for this project. The application, which can run on a tablet computer, includes the basic concept of air traffic control and an overview of four visual scanning strategies. Data were collected from students at the University of Oklahoma and analyzed. It turns out that the students were able to use the circular scanning strategy most consistently, they also reported that the circular strategy was the most helpful to detect potential conflict pair(s) of aircraft.

This project was funded by Federal Aviation Administration and led by Dr. Ziho Kang. I assisted in creating visual materials and strucutres of the application, and conducting experiment on both collecting users' peformance and usability of the app.

An en-route radar display is a type of radar display that provides information about aircraft en route to an airport to air traffic controllers. As part of our lab's research, we developed multiple measures that can be used to define and quantify the controllers' performance. These measures can be easily calculated or captured from a recording of the radar display while the controllers are engaged. The newly suggested performance measures include, but are not limited to, "time to detect a conflict pair of aircraft," "distance to a conflict point from each aircraft of the conflict pair," and "number of eye fixations on each aircraft of the conflict pair.” By measuring and analyzing the performance of air traffic controllers using these measures, we can identify areas where improvements can be made and develop strategies to optimize their performance. This information can be used to inform the design of training programs and improve the safety and efficiency of air traffic control systems.

As part of Human Factors and Simulation Lab's research work, we worked with the Federal Aviation Administration (FAA) to conduct a study on the eye movements of active air traffic controllers. Specifically, we collected data on their eye movements during their tasks in a high-fidelity virtual environment of an air traffic control tower. Our study aimed to gain insights into the behavior of air traffic controllers, particularly in a simulated environment. By analyzing their eye movements, we sought to understand how they process information and make decisions while performing their duties. The study involved the use of advanced eye tracking technology to capture and record the eye movements of the air traffic controllers while they carried out their tasks. The virtual environment was designed to be as realistic as possible, with the aim of simulating the experience of working in an actual air traffic control tower. Overall, our study provides valuable insights into the behavior of air traffic controllers and their decision-making processes. The findings can be used to inform the design of training programs and tools for air traffic controllers, with the aim of improving their performance and safety.