Volume 39 Issue 1
Feb.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(1): 26-34
LI Jipu, HE Yi, SUN Changxin, PENG Jianhua, CHEN Tao. An Acceptance Model and Risk Analysis of Automated Vehicles Based on SEM[J]. Journal of Transport Information and Safety, 2021, 39(1): 26-34. doi: 10.3963/j.jssn.1674-4861.2021.01.0004
Citation: LI Jipu, HE Yi, SUN Changxin, PENG Jianhua, CHEN Tao. An Acceptance Model and Risk Analysis of Automated Vehicles Based on SEM[J]. Journal of Transport Information and Safety, 2021, 39(1): 26-34. doi: 10.3963/j.jssn.1674-4861.2021.01.0004
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An Acceptance Model and Risk Analysis of Automated Vehicles Based on SEM

doi: 10.3963/j.jssn.1674-4861.2021.01.0004
  • 1.

    Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China

  • 2.

    Engineering Research Center for Transportation Safety of Ministry of Education, Wuhan University of Technology, Wuhan 430063, China

  • 3.

    Academy of Transportation Sciences, Ministry of Transport, Beijing 100029, China

  • 4.

    CATARC Automotive Testing Center (Wuhan) Co., Ltd., Wuhan, 430056, China

  • Received Date: 2020-12-04
  • Publish Date: 2021-02-28
    Abstract
  • A model is developed to accept automated vehicles based on the TAM model to study public acceptance of automated vehicles and its influencing factors. The relationship among external variables, latent variables, cognitive variables, and social acceptance of automated vehicles assumed in the model is verified by Pearson and Kendall correlations. A linear regression model and an acceptance-based structural equation model are established to explore the relationships of relevant factors, various variables, and public acceptance of automated vehicles. The results show that the cognition of legal ethics positively affects the acceptance intention of automated vehicles(E =0.038, and P < 0.001). Driving age and driving frequency negatively affect the acceptance of automated vehicles(E =-0.044, and P < 0.001). Educational background has a significant positive impact on the acceptance of automated vehicles by promoting the public's positive cognition and suppressing the negative cognition(E =0.172, and P < 0.001). Functional cognition has a significant positive impact on the acceptance intention of automated vehicles(E =0.444, and P < 0.001)

     

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