The interface challenge for partially automated vehicles: How driver characteristics affect information usage over time

Understanding how best to present information inside a partially automated vehicle is a prevalent challenge in Human-Machine Interface (HMI) design. To date little is known about how characteristics around trust, driving experience and cognitive workload specifically affect the types of information that should be presented in an automated vehicle. It is also unknown how these requirements change with increasing familiarity with the system.This twopart driving simulator study aimed to understand how trust and perceived workload changed with increasing exposure to a partially automated vehicle and how this corelated with information usage. Forty-four participants experienced nine partially automated simulated driving scenarios over the course of three or five consecutive sessions across the two studies. Eye tracking was used to record the information observed. Participants were asked to complete the Jian Trust Questionnaire, Driver Behaviour Questionnaire (DBQ) and the Driver Activity Load Index (DALI). Significant changes to trust and perceived workload were observed. Workload was found to decrease with lower fixations to information around the monitoring task.Drivers who were more prone to lapses or errors (as measured by the DBQ) tended towards less cognitively demanding information (skill based). This study has contributed to a better understanding of how driver characteristics can affect information use inside partially automated vehicles and such factors must be considered in future HMI design.