IEEE Access (Jan 2020)

Factors Influencing the User Acceptance of Automated Vehicles Based on Vehicle-Road Collaboration

  • Mingyang Deng,
  • Yingshi Guo,
  • Rui Fu,
  • Chang Wang

DOI
https://doi.org/10.1109/ACCESS.2020.3011033
Journal volume & issue
Vol. 8
pp. 134151 – 134160

Abstract

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The development of smart highway and vehicle-road collaboration has stimulated the market applications of automated vehicles. However, consumer acceptance of automated vehicles will influence the time course of automated driving technology promotion. This research explores user acceptance and demand for automated vehicles based on vehicle-road collaboration and identifies which factors drive the acceptance of automated vehicles. A sample of 3900 questionnaires are obtained through classification sampling. The descriptive statistical analysis of 3594 effective multi-source sample data shows that the user acceptance of automated vehicles based on the vehicle-road collaborative environment is 70.94%. The results show that the five categories of groups have significant differences in the acceptance of automated vehicles, and the focus on individual variables is higher than the overall acceptance. Due to the contradiction and dependence among various variables, multiple regression analysis is introduced. The results show that the six variables of safety, practicability, economy, highly automated driving functions, vehicle-road collaborative fusion application, and after-sale service have a significant positive impact on the acceptance of automated vehicles. The reasons why these six factors affect user acceptance are then analyzed in depth. The fitting model and acceptance value range obtained by this research can be used for market research. The research findings provide data support and theoretical reference for the research and development, marketing, teaching, and servicing of autonomous driving technology.

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