Symbol Salience Affects Change Detection Performance in General Aviation Weather Displays

Abstract

General aviation pilots perform many tasks during a flight such as navigating a route, performing 'see and avoid', operating the radio and navigational instruments, viewing charts and approach plates, and scanning and interpreting their flight instruments. In addition to these tasks, pilots may utilize a cockpit weather presentation to monitor weather information for areas along the route of flight. Due to the complexity of most modern weather displays, information changes may go unnoticed. The objective of this study was to examine how saliency characteristics such as line color, thickness, and orientation affected an observer’s change detection performance and response time. The study divided the sample population into three groups which were each designated a color of either black, red, or blue. The participants then completed a part-task change detection experiment where their ability to distinguish changes between images was measured, along with their response times for each trial. Upon completion of the experiment, the data was analyzed using Bayesian Signal Detection Theory. The key finding of this study was that change detection performance was best for objects with higher saliency levels in both the line color and thickness cases.