Modeling and Analysis of Color in a Multiple Attribute Task Battery Simulation for Human-Machine Teaming
ARAM ABUBAKER, development of a Color Model Analyzer for Modeling and Analyzing Color in a Multiple Attribute Task Battery Simulation for Human-Machine Teaming (under the direction of Dr. Charles D. McCurry). In Human Machine Teaming (HMT), human and machine collaborate with one another to accomplish a common goal or task. In complex HMT applications, chances of stress, human error, and fatigue is very high when humans operate advanced machine which sometimes may cause financial loss or even the loss of human life. The purpose of this dissertation is controlling human cognitive state by developing a dynamic color scheme for human machine interfaces to increase human performance, productivity and decrease human errors. Studies have shown that color can influence human performance and mood. In this study, a color model is developed for the TSU-MATB simulator to investigate color correlation with human performance. An experiment is designed to collected human performance and color information. Results show that the experimental setup produced minor changes on color with respect to performance and such data was not conducive to machine learning. An alternative color selection method was developed to select a color for a performance range based on the majority of the votes for the colors of each task.
Computer Engineering|Artificial intelligence
"Modeling and Analysis of Color in a Multiple Attribute Task Battery Simulation for Human-Machine Teaming"
ETD Collection for Tennessee State University.