Abstract
This work investigates the applicability of the elaboration likelihood model and its dual process mechanism to explain how features of the automated driving experience are perceived and, in turn, are processed by passengers to evaluate the driving experience in terms of passenger well-being. For this purpose, a user study with real-world experience of automated driving using a Wizard of Oz prototype was conducted. Eighty-four participants were assigned randomly to four different groups of elaboration likelihood by manipulating their motivation and ability to perceive and process features of the automated driving experience. Results indicate that the elaboration likelihood model and its two routes of processing apply to automated driving. Participants with higher levels of elaboration likelihood perceived more features of the driving experience, spent more cognitive effort on processing them, and consulted a larger variety of passenger needs to determine the effect of features on passenger well-being. Understanding the underlying mechanism of how passengers perceive and process features of automated vehicles may assist in design decisions of such vehicles to create a pleasant experience, high levels of passenger well-being, and ultimately boost the acceptance and willingness to use automated vehicles.
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The authors would like to thank AUDI AG, Germany, for their contribution to this research. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the views of AUDI AG, Germany.
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Sauer, V., Mertens, A., Reiche, M., Mai, C., Heitland, J., Nitsch, V. (2020). Perception and Processing in Automated Driving – A Dual Process Application. In: Stephanidis, C., Duffy, V.G., Streitz, N., Konomi, S., Krömker, H. (eds) HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments. HCII 2020. Lecture Notes in Computer Science(), vol 12429. Springer, Cham. https://doi.org/10.1007/978-3-030-59987-4_14
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