Autonomous driving has the potential to positively impact the daily life of humans. Techniques such as imaging processing, computer vision, and remote sensing have been highly involved in creating reliable and secure robotic cars. Conversely, the interaction between human perception and autonomous driving has not been deeply explored. Therefore, the analysis of human perception during the cognitive driving task, while making critical driving decisions, may provide great benefits for the study of autonomous driving. To achieve such an analysis, eye movement data of human drivers was collected with a mobile eye-tracker while driving in a automotive simulator built around an actual physical car, that mimics a realistic driving experience. Initial experiments have been performed to investigate the potential correlation between the driving behaviors and fixation patterns of the human driver.
Mingming Wang, Kate Walders, Martin E. Gordon, Jeff B. Pelz, Susan Farnand, "Auto-simulator Preparation for Research into Assessing the Correlation Between Human Driving Behaviors and Fixation Patterns" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines, 2018, pp 163-1 - 163-6, https://doi.org/10.2352/ISSN.2470-1173.2018.17.AVM-163