This study attempts to identify critical Key Performance Indicators (KPIs) to assess the safety and general impact of fluid interactions between the user and Human Machine Interfaces (HMIs) within automated vehicles. More specifically, safety, driving performance, and general impact indicators were considered for such an assessment. The identification of KPIs was based on a literature review, previous knowledge obtained from similar research programs and a hazard identification process. The derived KPIs were categorized into two main categories, namely safety and general impact, and these categories were distinguished in 11 additional subcategories. The most critical KPIs within the safety group were found to be take-over time as well as the number of take-overs, whereas comfort, the feeling of safety and trust were the most crucial impact-related KPIs. Nevertheless, validation of those KPIs in field trials is, however, deemed necessary.
|Tags||driver behaviour, statistical modelling, traffic automation|