Data underlying the publication: Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles

This dataset is derived from a driving simulator study that explored the dynamics of perceived risk and trust in the context of driving automation. The study involved 25 participants who were tasked with monitoring SAE Level 2 driving automation features (Adaptive Cruise Control and Lane Centering) while encountering various driving scenarios on a motorway. These scenarios included merging and hard-braking events with different levels of criticality. This dataset contains kinetic data from the driving simulator, capturing variables such as vehicle position, velocity, and acceleration among others. Subjective ratings of perceived risk and trust, collected post-event for regression analysis are also included.