Transparency Assessment on Level 2 Automated Vehicle HMIs

Yuan Cheng Liu, Nikol Figalová, Klaus Bengler

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

4 Zitate (Scopus)

Abstract

The responsibility and role of human drivers during automated driving might change dynamically. In such cases, human-machine interface (HMI) transparency becomes crucial to facilitate driving safety, as the states of the automated vehicle have to be communicated correctly and efficiently. However, there is no standardized transparency assessment method to evaluate the understanding of human drivers toward the HMI. In this study, we defined functional transparency (FT) and, based on this definition, proposed a transparency assessment method as a preliminary step toward the objective measurement for HMI understanding. The proposed method was verified in an online survey where HMIs of different vehicle manufacturers were adopted and their transparencies assessed. Even though no significant result was found among HMI designs, FT was found to be significantly higher for participants more experienced with SAE Level 2 automated vehicles, suggesting that more experienced users understand the HMIs better. Further identification tests revealed that more icons in BMW’s and VW’s HMI designs were correctly used to evaluate the state of longitudinal and lateral control. This study provides a novel method for assessing transparency and minimizing confusion during automated driving, which could greatly assist the HMI design process in the future.

OriginalspracheEnglisch
Aufsatznummer489
FachzeitschriftInformation (Switzerland)
Jahrgang13
Ausgabenummer10
DOIs
PublikationsstatusVeröffentlicht - Okt. 2022

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