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Benefits of Personalization in the Context of a Speech-Based Left-Turn Assistant

Dennis Orth, Nadja Schömig, Christian Mark, Monika Jagiellowicz-Kaufmann, Dorothea Kolossa, Martin Heckmann, "Benefits of Personalization in the Context of a Speech-Based Left-Turn Assistant", Proceedings of the 9th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI ’17), pp. 193-201, 2017.


We have previously introduced a novel Assistance On Demand (AOD) concept in the context of an urban speech-based left-turn assistant which supports the driver in monitoring and decision making by providing recommendations for suitable time gaps to enter the intersection. In a first user study participants showed a clear preference for the AOD system, yet also frequently mentioned that the recommended gaps did not fit their driving behavior. In the user study we present here, we investigate in how far the acceptance and efficiency of the AOD system can be increased by a personalization of the recommended gaps to the individual driver. For this purpose, we estimate individual drivers' gap acceptance from observations of their manual driving and use it to evaluate a default and a personalized variant of the AOD system. Results reveal a clear preference for the personalized assistant compared to the default one and to driving manually.

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