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    Research on Interference-Free Monitoring of Driver's Steering Behavior

    Research on Interference-Free Monitoring of Driver's Steering Behavior


    The study of driver's driving behavior is not only an important part of traffic safety, but also of great significance to promoting the development of autonomous vehicles. In this paper, a Triboelectric Nanogenerators (AK-TENG) with an aluminum (AI)-Kapton friction layer structure is developed for driving behavior monitoring of drivers. AK-TENG has high sensitivity and certain flexibility. Compared with ordinary Triboelectric Nanogenerators, the structure is stronger and more stable, and less damaged. It is used to obtain the driving behavior data of the driver on the steering wheel. This paper uses AK-TENG to obtain driving behavior information data to monitor the driver's steering behavior, and also provides a new idea for the design of high-sensitivity self-powered sensors in intelligent transportation systems.

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    Titel :

    Research on Interference-Free Monitoring of Driver's Steering Behavior

    Weitere Titelangaben:

    Lect. Notes Electrical Eng.

    Beteiligte:
    Wang, Wuhong (Herausgeber:in) / Wu, Jianping (Herausgeber:in) / Jiang, Xiaobei (Herausgeber:in) / Li, Ruimin (Herausgeber:in) / Zhang, Haodong (Herausgeber:in) / Zhang, Haodong (Autor:in) / Tan, Haiqiu (Autor:in) / Feng, Kuikui (Autor:in) / Shi, Jian (Autor:in) / Sun, Dongxian (Autor:in)
    Kongress:

    International Conference on Green Intelligent Transportation System and Safety ; 2021 November 19, 2021 - November 21, 2021

    Erschienen in:

    Green Transportation and Low Carbon Mobility Safety ; Kapitel : 35 ; 501-508

    Lecture Notes in Electrical Engineering ; 944

    Erscheinungsdatum :

    2022-10-28

    Format / Umfang :

    8 pages

    ISBN :

    978-981-19-5615-7 , 978-981-19-5614-0

    ISSN :

    1876-1119 , 1876-1100

    DOI :

    https://doi.org/10.1007/978-981-19-5615-7_35

    Medientyp :

    Aufsatz/Kapitel (Buch)

    Format :

    Elektronische Ressource

    Sprache :

    Englisch

    Schlagwörter :

    Intelligent traffic system , Driving behavior monitor , Triboelectric nanogenerator Engineering , Transportation Technology and Traffic Engineering , Computational Intelligence , Automotive Engineering , Energy Policy, Economics and Management , Mechanical Engineering

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