Autonomous driving technology is an important direction in vehicle engineering research, and acceptance, as a reflection of public attitudes toward vehicles, is the basis for promoting the marketing of the technology. The results of recent acceptance surveys have gradually decreased, and acceptance may be related to recent traffic accidents. To explore the influencing factors of declining acceptance, the authors introduced the safety risk factors of autonomous driving and proposed an improved model based on the combination of TPB and TAM for acceptance interpretation and prediction. By analyzing the model and data results statistically, it is verified that safety risk has an impact on acceptance and a more significant impact on actual behavior. It is concluded that people's misunderstanding of unreasonable factors or irrational factors about the safety of autonomous driving technology needs to be eliminated in order to improve public acceptance and promote the accelerated implementation of autonomous driving technology.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Application of data analysis in autonomous driving technology acceptance studies


    Contributors:
    Deng, MingYang (author) / Guo, YuXi (author) / Guo, YingShi (author) / Zhao, Xia (author)

    Conference:

    4th International Conference on Informatics Engineering & Information Science (ICIEIS2021) ; 2021 ; Tianjin,China


    Published in:

    Proc. SPIE ; 12161


    Publication date :

    2022-02-14





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Autonomous Car Acceptance: Safety vs. Personal Driving Enjoyment

    Ernst, Claus-Peter Hermann / Reinelt, Patrick | British Library Conference Proceedings | 2017


    Bus driver’s technology acceptance for driving assistants

    Gruchmann, Tim / Pratt, Nadine / Salzmann, Axel et al. | DataCite | 2021

    Free access

    A Framework to Study Autonomous Driving User Acceptance in the Wild

    Gabrielli, Alessandro / Mentasti, Simone / Manzoni, Gabriel Esteban et al. | TIBKAT | 2022


    Passengers’ Emotions Recognition to Improve Social Acceptance of Autonomous Driving Vehicles

    Sini, Jacopo / Marceddu, Antonio Costantino / Violante, Massimo et al. | Springer Verlag | 2020


    Passengers’ Emotions Recognition to Improve Social Acceptance of Autonomous Driving Vehicles

    Sini, Jacopo / Marceddu, Antonio Costantino / Violante, Massimo et al. | BASE | 2020

    Free access