基于SEM的自动驾驶汽车接受度模型与风险分析

为了探究社会大众对自动驾驶汽车的接受度及其影响因素，通过对自动驾驶汽车的风险评估，基于TAM模型增加外部变量，改进感知易用性与感知有用性，建立自动驾驶汽车接受度研究模型。将研究模型中假设的外部变量、潜在变量、认知变量与自动驾驶汽车社会接受度的关系进行Pearson相关性与Kendall相关性检验。基于相关性检验剔除无关因素变量，建立线性回归模型，对相关因素与自动驾驶汽车接受度的关系进行了探究，并以此建立接受度结构方程模型，对各个变量与自动驾驶汽车社会接受度之间的因果关系进行了进一步研究论证。结果显示，法律伦理的认知对自动驾驶汽车接受意向产生（E =0.038，P < 0.001）显著正影响。驾龄、驾车频率对接受意向产生（E =-0.044，P < 0.001）显著负影响。学历通过促进公众对自动驾驶汽车正面的认知、抑制负面认知，从而对公众接受意向产生（E =0.172，P < 0.001）显著正影响。功能的认知会促进公众对自动驾驶汽车正面影响的认知，从而对接受意向产生（E =0.444，P < 0.001）显著正影响。 

An Acceptance Model and Risk Analysis of Automated Vehicles Based on SEM

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)