Analyzing of Impact Factors of Residents' Choice of Autonomous Vehicle: A Network Questionnaire Survey in Nanchang, China

Abstract

Autonomous vehicle technologies provide effective opportunities to improve the driving environment and reduce the number of traffic accidents. However, due to technical limitations and social ethics challenges, the acceptance and recognition of autonomous driving among residents still need to be improved. For this purpose, a network questionnaire survey with 251 volunteers was conducted in Nanchang, China. The impact factors such gender, age, education, income and others, which may associated with the residents' choice of autonomous vehicle were collected. Three indexes which included the degree of residents' satisfaction and acceptance were adapted to calibrate the reported residents' choice. A multiple linear regression model was applied to identify significant factors and to establish the identification model. The results indicated that the type of driver's license, passenger's comfort and safety and the age of driver with license are significant positive correlated to residents' satisfaction in the data (Approx. Sig<0.01). In addition, the relationship between curiosity, expectation, desire to buy and residents' acceptance is positive correlation (Approx. Sig<0.01). The identification model also demonstrated a high predictive power with a prediction accuracy of 0.80. The conclusions provide theoretical support for improving residents' acceptance and satisfaction with autonomous vehicle, and promote the marketization operation of self-driving technology.