Reflecting the automated vehicle's perception and intention: Light-based interaction approaches for on-board HMI in highly automated vehicles

Abstract

The number of automated driving functionalities in conventional vehicles is rising year by year. Intensive research regarding highly automated vehicles (AV) is performed by all big OEMs. AVs need advanced sensors and intelligence to detect relevant objects in driving situations and to perform driving tasks safely. Due to the shift of control, the role of the driver changes to an on-board user without any driving related tasks. However, the interaction between the AV and its on-board user stays vital in terms of creating a common understanding of the current situation and establishing a shared representation of the upcoming manoeuvre to ensure user acceptance and trust in automation. The current paper investigates two different light-based HMI approaches for AV / on-board user interaction. In a VR-Study 33 participants experienced an automated left turn in an urban scenario in highly automated driving. While turning, the AV had to consider other road users (pedestrian or another vehicle). The two HMI approaches (intention- vs. perception-based) were compared to a baseline using a within-subject design. Results reveal that using perception- or intention-based interaction design lead to higher user trust and usability in both scenarios.