The Effects of a Predictive HMI and Different Transition Frequencies on Acceptance, Workload, Usability, and Gaze Behavior During Urban Automated Driving Automated driving research as a key topic in the automotive industry is currently undergoing change. Research is shifting from unexpected and timecritical takeover situations to human machine interface (HMI) design for predictable transitions. Furthermore, new applications like automated city driving are getting more attention and the ability to engage in nondriving related activities (NDRA) starting from SAE Level 3 automation poses new questions to HMI design. Moreover, future introduction scenarios and automated capabilities are still unclear. Thus, we designed, executed, and assessed a driving simulator study focusing on the effect of different transition frequencies and a predictive HMI while freely engaging in naturalistic NDRA. In the study with 33 participants, we found transition frequency to have effects on workload and acceptance, as well as a small impact on the usability evaluation of the system. Trust, however, was not affected. The predictive HMI was used and accepted, as can be seen by eyetracking data and the poststudy questionnaire, but could not mitigate the abovementioned negative effects induced by transition frequency. Most attractive activities were window gazing, chatting, phone use, and reading magazines. Descriptively, window gazing and chatting gained attractiveness when interrupted more often, while reading magazines and playing games were negatively affected by transition rate.

Information Needs and Visual Attention during Urban, Highly Automated Drivingxe2x80x94An Investigation of Potential Influencing Factors During highly automated driving, the passenger is allowed to conduct nondriving related activities (NDRA) and no longer has to act as a fallback at the functional limits of the driving automation system. Previous research has shown that at lower levels of automation, passengers still wish to be informed about automated vehicle behavior to a certain extent. Due to the aim of the introduction of urban automated driving, which is characterized by high complexity, we investigated the information needs and visual attention of the passenger during urban, highly automated driving. Additionally, there was an investigation into the influence of the experience of automated driving and of NDRAs on these results. Forty participants took part in a driving simulator study. As well as the information presented on the humanxe2x80x93machine interface (system status, navigation information, speed and speed limit), participants requested information about maneuvers, reasons for maneuvers, environmental settings and additional navigation data. Visual attention was significantly affected by the NDRA, while the experience of automated driving had no effect. Experience and NDRA showed no significant effect on the need for information. Differences in information needs seem to be due to the requirements of the individual passenger, rather than the investigated factors.