Dr. John R Sullins' Research: Eye Tracking & Autonomous Navigation

Eye Tracking for learned decision making at intersections: The goal of this project is to use wearable eye trackers to isolate the sections of images that human drivers most commonly focus on when approaching an intersection. This data will be used to generate training examples that only contain sections of the images corresponding to those areas most commonly observed by human drivers. These will be used to train a neural network configured for deep learning to make correct decisions when approaching intersections. This project is currently supported by a University Research Council grant.