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Communication of Intentions in Automated Driving – the Importance of Implicit Cues and Contextual Information on Freeway Situations

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12791))

Abstract

In manual driving, implicit cues play an important role in the communication of intention and anticipation of upcoming driving situations. Considering mixed traffic situations, all interaction partners need to be able to detect and interpret implicit cues, as they are central to design smooth, efficient, and safe driving styles. However, most current automated driving functions do not incorporate the communication and anticipation of implicit cues. The lack of anticipation of upcoming events in automated driving increases the probability of inadequate actions (e.g., sudden breaking maneuver). This concerns especially freeway situations as the driving speeds are considerable high, requiring more anticipation. To show the importance of implicit cues, a study on German freeway was conducted where over 1000 km of 360° video material was recorded. The video material was then annotated with the focus on the identification of situations where implicit cues can be observed. Beside the situations, implicit and explicit cues as well as contextual information were annotated, too. The results show i) that specific situations can be categorized where ii) implicit and explicit as well as contextual information can be identified. Beside the findings of the study, the article provides an outlook on a naturalistic driving study design to examine implicit cues during the drive.

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Acknowledgements

The research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 416228727 – SFB 1410.

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Correspondence to Konstantin Felbel .

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Felbel, K., Dettmann, A., Lindner, M., Bullinger, A.C. (2021). Communication of Intentions in Automated Driving – the Importance of Implicit Cues and Contextual Information on Freeway Situations. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2021. Lecture Notes in Computer Science(), vol 12791. Springer, Cham. https://doi.org/10.1007/978-3-030-78358-7_17

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  • DOI: https://doi.org/10.1007/978-3-030-78358-7_17

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