Effect of Visualization of Pedestrian Intention Recognition on Trust and Cognitive Load

Abstract

Autonomous vehicles carry the potential to greatly improve mobility and safety in traffic. However, this technology has to be accepted and of value for the intended users. One challenge on this way is the detection and recognition of pedestrians and their intentions. While there are technological solutions to this problem, there seems to be no research on how to make this information transparent to the user in order to calibrate the user's trust. Our work presents a comparative study of 5 visualization techniques with Augmented Reality or tablet-based visualization technology and two or three information clarity states of pedestrian intention in the context of highly automated driving. We investigated these in a user study in Virtual Reality (N=15). We found that such a visualization was rated reasonable, necessary, and that especially the Augmented Reality-based version with three clarity states was preferred.