Web: http://arxiv.org/abs/2209.10536

Sept. 22, 2022, 1:12 a.m. | Zhaobo K. Zheng, Kumar Akash, Teruhisa Misu, Vidya Krishmoorthy, Miaomiao Dong, Yuni Lee, Gaojian Huang

cs.LG updates on arXiv.org arxiv.org

A key factor to optimal acceptance and comfort of automated vehicle features
is the driving style. Mismatches between the automated and the driver preferred
driving styles can make users take over more frequently or even disable the
automation features. This work proposes identification of user driving style
preference with multimodal signals, so the vehicle could match user preference
in a continuous and automatic way. We conducted a driving simulator study with
36 participants and collected extensive multimodal data including behavioral, …

arxiv driving identification

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