Automated driving is on the advance and is linked to benefits such as an increasing comfort for the driver as well as safety promotion and rising fuel and transport efficiency. Due to the rising level of automation, drivers will become more and more excluded from their actual driving task resulting in phenomena such as an inadequate level of trust in the automated system or a lack of accurate knowledge about the system's capabilities and limitations. This paper describes a study on evaluating a system transparent human-machine-interface that offers information about the longitudinal automation's current state and actions. To promote transparency, an approach of system confidence information (SCI) has been developed. Linear mixed models reveal that the presentation of SCI decreases braking reaction time in the case of automation failure, and in addition indicate improved situation awareness. The experimental results provide support for the hypothesis that presentation of system confidence information improves the driver-automation cooperation

Vehicle automation is linked to various benefits, such as increase in fuel and transport efficiency as well as increase in driving comfort. However, automation also comes with a variety of possible downsides, e.g., loss of situational awareness, loss of skills, and inappropriate trust levels regarding system functionality. Drawbacks differ at different automation levels. As highly automated driving (HAD, level 3) requires the driver to take over the driving task in critical situations within a limited period of time, the need for an appropriate human–machine interface (HMI) arises. To foster adequate and efficient human–machine interaction, this contribution presents a user-centered, iterative approach for HMI evaluation of highly automated truck driving. For HMI evaluation, a driving simulator study [n = 32] using a dynamic truck driving simulator was conducted to let users experience the HMI in a semi-real driving context. Participants rated three HMI concepts, differing in their informational content for HAD regarding acceptance, workload, user experience, and controllability. Results showed that all three HMI concepts achieved good to very good results in these measures. Overall, HMI concepts offering more information to the driver about the HAD system showed significantly higher ratings, depicting the positive effect of additional information on the driver–automation interaction.

Vehicle automation is linked to various benefits such as an increase in fuel and transport efficiency, as well as an increase in driving comfort. Automation also comes with a variety of downsides e.g. loss of situation awareness, loss of skills as well as inappropriate trust levels regarding system functionality. Drawbacks differ between automation levels. As highly-automated driving (level 3) requires the driver to take over the driving task in critical situations within a limited period of time, the need for an appropriate human-machine interface (HMI) arises. To foster adequate and efficient humanmachine interaction, this contribution presents a user-centered, iterative approach for HMI design for highly-automated truck driving.An expert workshop was conducted to develop first ideas and HMI ketches. Workshop results were combined with scientific findings regarding HMI design for highly-automated car driving. Based on those findings, a paper prototype was created and evaluated with experts, using an approach of mixed qualitative methods (heuristic evaluation, thinking aloud). The outcome was implemented to the HMI concept. In a third step, the HMI was conceptualized as video prototype enabling a more detailed evaluation. Again, experts were asked to assess the HMI using qualitative (thinking aloud) and quantitative methods (questionnaires).The result represents a video prototype showing a HMI strategy for highly-automated driving, aiming at fostering a successful human-machine interaction. Relevant issues such as drivers' informational needs, situation awareness and trust were explicitly considered during HMI design. Next steps comprise HMI implementation and user evaluation in a driving simulator to let users experience the HMI in a semi-real driving context.