Towards Transparent Behavior of Automated Vehicles: Design and Evaluation of HUD Concepts to Support System Predictability through Motion Intent Communication

Abstract

In automated vehicles, it is essential to feedforward motion intentions to users so that they understand the vehicle's actions. Otherwise, non-transparency limits situation awareness and leads to mistrust. In this work, we are communicating the vehicle's actions to the user either by displaying icons (planar HUD) or through augmented reality (contact-analog HUD) to increase transparency. We developed both concepts in a user-centered design process. Further, we evaluated them in two subsequent user studies (N = 27). In the first study, we focused on UX and trust in higher automation levels (cf. SAE level 3-5). In the second study, we focused on safety and error prevention in lower automation levels (cf. SAE levels 1-2). Our results show that both visualizations increase UX and trust in an automated system. Nevertheless, the AR approach outperforms the icon-based approach by achieving higher user experience as well as faster and less error-prone take-overs of participants.