Efficient Information Representation Method for Driver-Centered AR-HUD System

Providing a suitable and efficient representation of a driver’s perspective is a way to reduce traffic accidents. In this paper, we first introduce a driver-centered AR (augmented-reality) HUD (head-up-display) system that superimposes augmented virtual objects onto a real scene under all types of driving situations including unfavorable weather (such as rainy, foggy, overcast, and snowy) conditions. We next explain the scenario and method used in our comparative experiments on a method for improving both the cognitive usability and visibility of drivers. For this, we comparatively analyzed not only information display locations but also information representation for six information types using a driving simulator with thirty subjects. For the effects on safety, the situational driver awareness of safety-related road events was measured. To determine the differences in the visual cognitive workload placed upon drivers, we tracked their eye movements. The subjective workload of the participants was assessed using the RSME (Rating Scale Mental Effort).