Informing Design of In-Vehicle Augmented Reality Head-Up Displays and Methods for Assessment

Drivers require a steady stream of relevant but focused visual input to make decisions. Most driving information comes from the surrounding environment so keeping drivers' eyes on the road is paramount. However, important information still comes from in-vehicle displays. With this in mind, there has been renewed recent interest in delivering driving in-formation via head-up display. A head-up display (HUD) can present an image directly on-to the windshield of a vehicle, providing a relatively seamless transition between the display image and the road ahead. Most importantly, HUD use keeps drivers' eyes focused in the direction of the road ahead. The transparent display coupled with a new location make it likely that HUDs provide a fundamentally different driving experience and may change the way people drive, in both good and bad ways. Therefore, the objectives of this work were to 1) understand changes in drivers' glance behaviors when using different types of displays, 2) investigate the impact of HUD position on glance behaviors, and 3) examine the impact of HUD graphic type on drivers' behaviors. Specifically, we captured empirical data regarding changes in driving behaviors, glance behaviors, reported workload, and preferences while driving performing a secondary task using in-vehicle displays.

We found that participants exhibited different glance behaviors when using different display types, with participants allocating more and longer glances towards a HUD as compared to a traditional Head-Down Display. However, driving behaviors were not largely affected and participants reported lower workload when using the HUD. HUD location did not cause large changes in glance behaviors, but some driving behaviors were affected. When exam-ining the impact of graphic types on participants, we employed a novel technique for ana-lyzing glance behaviors by dividing the display into three different areas of interest relative to the HUD graphic. This method allowed us to differentiate between graphic types and to better understand differences found in driving behaviors and participant preferences than could be determined with frequently used glance analysis methods. Graphics that were fixed in place rather than animated generally resulted in less time allocated to looking at the graphics, and these changes were likely because the fixed graphics were simple and easy to understand. Ultimately, glance and driving behaviors were affected at some level by the display type, display location, and graphic type as well as individual differences like gender and age.