  Human-machine Interface (HMI) is critical for safety during automated
driving, as it serves as the only media between the automated system and human
users. To enable a transparent HMI, we first need to know how to evaluate it.
However, most of the assessment methods used for HMI designs are subjective and
thus not efficient. To bridge the gap, an objective and standardized HMI
assessment method is needed, and the first step is to find an objective method
for workload measurement for this context. In this study, two
psychophysiological measures, electrocardiography (ECG) and electrodermal
activity (EDA), were evaluated for their effectiveness in finding differences
in mental workload among different HMI designs in a simulator study. Three HMI
designs were developed and used. Results showed that both workload measures
were able to identify significant differences in objective mental workload when
interacting with in-vehicle HMIs. As a first step toward a standardized
assessment method, the results could be used as a firm ground for future
studies. Marie Sk{\l}odowska-Curie Actions; Innovative Training Network (ITN);
SHAPE-IT; Grant number 860410; Publication date: [29 Sep 2023]; DOI:
[10.54941/ahfe1004172]
