Abstract
Drivers tend to glance at the display of in-car infotainment systems despite the presence of speech output. The SEEV Model by Wickens et al. (2003) defines parameters influencing attention allocation towards events in dynamic environments. Analysing the SEEV Model provides insights on which of the parameters of the SEEV Model speech output has disadvantages compared to visual output. In two driving simulator experiments, it was tested whether increasing or decreasing the deducted parameters of the SEEV Model for speech output by means of improving the speech output in various respects actually decreases attention allocation to the display. It was shown that increasing the relevant information content (corresponding to the parameters expectancy and value) for speech as well as decreasing the time effort (which corresponds to the parameter effort) of speech compared to a baseline condition leads towards lower percentage dwell time to the display. Next, it was shown that a conscious motor action performed to request for speech output (corresponding to the parameter effort) decreases attention allocation towards the display in situations whereby the secondary task gets interrupted by a highly demanding driving task. Based on theses insights, design recommendations for speech output were deducted and implemented in a prototype with several infotainment applications. In another driving simulator experiment, it was observed that the design recommendations actually reduced attention allocation towards the display compared to a common speech output design of in-car infotainment systems. The design recommendations to reduce the time effort of speech output were again evaluated regarding their influence on the development of users’ mental models. Finally, it was tested whether increasing the hedonic quality of speech output also leads towards less time glancing at the display. On the one hand, the conducted experiments showed which parameters of the SEEV Model could be influenced for speech output to decrease attention allocation to the display of a multimodal in-car infotainment system. On the other hand, the results provided insights regarding the applicability of specific SEEV Model parameters to the auditory modality since so far the model had only been evaluated with respect to the visual modality. Finally, it was shown that also hedonic aspects of speech output do indeed influence attention allocation.
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