SOME ON-ROAD GLANCES ARE MORE EQUAL THAN OTHERS: MEASURING ENGAGEMENT IN THE DRIVING TASK

Abstract

The current work examines a methodology developed for assessing driver attention management using high-precision eye glances towards safety-relevant driving information. The Task Analysis Eye Movement Overlay (TAEMO) method uses task analyses, video recordings of a driving scenario, and eye glance data toward visual keys that drivers sample during the driving scenario to directly measure driver engagement. This methodology has applications for evaluating infrastructure design, driver impairment assessment, driver training, driver distraction research, and vehicle human-machine interface (HMI) system design.