Driving Difficulty Impacts ADAS Acceptance: A Multiple Linear Regression Analysis

After conducting initial predictive analysis on the driving difficulty variable, the results indicate that driving difficulty does indeed influence drivers' acceptance of ADAS. Consequently, a more in-depth analysis is performed using multiple linear regression to explore the relationships between various driving difficulties and the latent variable of ADAS acceptance.

Multiple linear regression is a commonly used statistical method to study the correlation between multiple independent variables and a dependent variable. It involves establishing a predictive model for continuous numerical variables. In this study, the psychological latent variable corresponding to drivers' acceptance of ADAS is transformed into a continuous numerical variable by taking the average of the corresponding observed variables. To investigate the impact of driving difficulties on the psychological latent variable of ADAS acceptance, a multiple linear regression model is employed to observe how drivers' willingness to use ADAS changes under the influence of driving difficulty factors.