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SAE level 2 and 3 semi-autonomous vehicles are widely available but, due to the nature of automation, their in-vehicle displays are required to communicate more complex information to the driver. Examination of interfaces from a variety of manufacturers revealed a clear lack of consistency in the way key information is displayed. Different manufacturers have adopted icons varying in shape and colour to convey the same message. When driving a semi-autonomous vehicle, mode awareness is critical for trust, performance and safety. Standardisation of icons has been shown to have many benefits including opening products up to wider international markets by helping overcome language and cultural barriers, by providing a method of communication which can surpass them. However, the current lack of standardisation in icon design could cause mode confusion and has little cross-vehicle compatibility. To understand the impact of mode confusion on users, a focus group was held in which participants were asked to interpret the meaning of icons from a variety of different driver interfaces. Ambiguity in user interpretations makes the case for the introduction of new ISO standard icons to better support drivers in SAE level 2 and 3 automated vehicles.

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This research aims to show the effectiveness of Operator Event Sequence Diagrams (OESDs) in the normative modelling of vehicle automation to human drivers’ handovers and validate the models with observations from a study in a driving simulator. The handover of control from automation to human operators has proved problematic, and in the most extreme circumstances catastrophic. This is currently a topic of much concern in the design of automated vehicles. OESDs were used to inform the design of the interaction, which was then tested in a driving simulator. This test provided, for the first time, the opportunity to validate OESDs with data gathered from videoing the handover processes. The findings show that the normative predictions of driver activity determined during the handover from vehicle automation in a driving simulator performed well, and similar to other Human Factors methods. It is concluded that OESDs provided a useful method for the human-centred automation design and, as the predictive validity shows, can continue to be used with some confidence. The research in this paper has shown that OESDs can be used to anticipate normative behaviour of drivers engaged in handover activities with vehicle automation in a driving simulator. Therefore, OESDs offer a useful modelling tool for the Human Factors profession and could be applied to a wide range of applications and domains.

Vehicles with SAE Level 2 automated features are already in active use on the road, and vehicles with Level 3 or 4 will be with us soon. Although the vehicles provide support for longitudinal and lateral control, partially automated driving experience is sometimes more demanding than manual driving. However, the effects of automated driving on workload in naturalistic conditions have not been extensively investigated, as most studies have been undertaken in driving simulators. This study aims to extend the current understanding about workload in partially automated driving on public roads. Drivers' perceived workload was assessed after conducting manual and automated driving activities using a small sample (N = 8). They performed driving tasks in three contemporary vehicles with SAE Level 2 features, in highway and urban environments. The comparative findings revealed that drivers' perceived workload was higher in partially automated driving than manual driving. Furthermore, perceived workload was higher in urban environments than highway environments and in less experienced drivers than more experienced drivers. Although the findings may need to be interpreted with caution due to the small sample size, they provide a future research agenda that can be built upon.