Road safety impact is critical for consideration during automation development. In combination with the fact that it is estimated that autonomous vehicles could reach up to 90% of the market share by 2050, it can be concluded that automation should be monitor in order for this transition to be as safer as possible. In this direction, this study aims to identify critical key performance indicators (KPIs) for safety assessment of autonomous vehicles through microscopic traffic simulation. For this purpose, a microscopic simulation analysis was conducted to provide multiple measurements quantifying the impacts of connected and autonomous vehicles (CAVs) in different traffic conditions. Critical safety KPIs were identified exploiting the microscopic simulation outputs in order to shed light on critical aspects that the quantification of safety needs. The obtained KPIs could guide stakeholders in optimizing the safety assessment procedures through simulation by emphasizing critical safety aspects.
|Tags||driver behaviour, statistical modelling, traffic automation, traffic simulation|