  Automated vehicle acceptance (AVA) has been measured mostly subjectively by
questionnaires and interviews, with a main focus on drivers inside automated
vehicles (AVs). To ensure that AVs are widely accepted by the public, ensuring
the acceptance by both drivers and passengers is key. The in-vehicle experience
of passengers will determine the extent to which AVs will be accepted by
passengers. A comprehensive understanding of potential assessment methods to
measure the passenger experience in AVs is needed to improve the in-vehicle
experience of passengers and thereby the acceptance. The present work provides
an overview of assessment methods that were used to measure a driver's
behavior, and cognitive and emotional states during (automated) driving. The
results of the review have shown that these assessment methods can be
classified by type of data-collection method (e.g., questionnaires, interviews,
direct input devices, sensors), object of their measurement (i.e., perception,
behavior, state), time of measurement, and degree of objectivity of the data
collected. A conceptual model synthesizes the results of the literature review,
formulating relationships between the factors constituting the in-vehicle
experience and AVA acceptance. It is theorized that the in-vehicle experience
influences the intention to use, with intention to use serving as predictor of
actual use. The model also formulates relationships between actual use and
well-being. A combined approach of using both subjective and objective
assessment methods is needed to provide more accurate estimates for AVA, and
advance the uptake and use of AVs.
