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Design of appropriate interaction and human–machine interfaces for the handover of control between vehicle automation and human driver is critical to the success of automated vehicles. Problems in this interfacing between the vehicle and driver have led, in some cases, to collisions and fatalities. In this project, Operator Event Sequence Diagrams (OESDs) were used to design the handover activities to and from vehicle automation. Previous work undertaken in driving simulators has shown that the OESDs can be used to anticipate the likely activities of drivers during the handover of vehicle control. Three such studies showed that there was a strong correlation between the activities drivers represented in OESDs and those observed from videos of drivers in the handover process, in driving simulators. For the current study, OESDs were constructed during the design of the interaction and interfaces for the handover of control to and from vehicle automation. Videos of drivers during the handover were taken on motorways in the UK and compared with the predictions from the OESDs. As before, there were strong correlations between those activities anticipated in the OESDs and those observed during the handover of vehicle control from automation to the human driver. This means that OESDs can be used with some confidence as part of the vehicle automation design process, although validity generalisation remains an important goal for future research. [ABSTRACT FROM AUTHOR]

Predicting what drivers will do as vehicle control is handed over to them from automation is a relatively new challenge for the motor vehicle industry. Operator Event Sequence Diagrams (OESDs) offer a way of modeling the interactions between the driver and vehicle automation in the handover of control. In this paper, two studies are presented in which a range of handover strategies are tested. The anticipated driver strategies were modeled using OESDs to serve as predictions of driver behavior. Drivers were then observed in two separate studies: (1) using a Lower‐Fidelity (vehicle seat and controls) simulator and (2) using a Higher‐Fidelity (whole vehicle) simulator. Driver behavior during a takeover task was categorized according to the signal detection paradigm into hits, misses, false alarms, and correct rejections. The results showed that for all strategies in both sets of studies, the median criterion for validity was exceeded (φ > 0.8), suggesting that OESDs made good predictions of driver behavior during the handover of the vehicle from automation to manual control. [ABSTRACT FROM AUTHOR]

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone. [ABSTRACT FROM AUTHOR]