  In conditionally automated vehicles, drivers can engage in secondary
activities while traveling to their destination. However, drivers are required
to appropriately respond, in a limited amount of time, to a take-over request
when the system reaches its functional boundaries. In this context, Virtual
Reality systems represent a promising training and learning tool to properly
familiarize drivers with the automated vehicle and allow them to interact with
the novel equipment involved. In this study, the effectiveness of an
Head-Mounted display (HMD)-based training program for acquiring interaction
skills in automated cars was compared to a user manual and a fixed-base
simulator. Results show that the training system affects the take-over
performances evaluated in a test drive in a high-end driving simulator.
Moreover, self-reported measures indicate that the HMD-based training is
preferred with respect to the other systems.
