Citation

Chen Y, Khalid Khan S, Shiwakoti N, Stasinopoulos P, Aghabayk K. Case Stud. Transp. Policy 2023; 14: e101072.

Copyright

(Copyright © 2023, World Conference on Transport Research Society, Publisher Elsevier Publishing)

DOI

10.1016/j.cstp.2023.101072

PMID

unavailable

Abstract

There has been an increasing trend in using user acceptance models to explore the public acceptance of automated vehicles (AVs) in different countries. Most of the previous studies have analysed perceived usefulness, behavioural attitude, subjective norms as well as perceived ease of use, but other important factors, such as trust and data privacy, have not been adequately considered. Likewise, public perceptions of fully AVs are limited in the literature as most studies focus on different levels of automation. This study aims to assess the behavioural intention to use fully AVs in Australia by extending the Technology Acceptance Model (TAM) that includes data privacy and trust in the TAM constructs. Based on a survey of 809 adult respondents from Australia, the model was evaluated with Structural Equation Modelling. The research revealed perceived trust and perceived data privacy is the first and second most important variable affecting the attitude, followed by perceived ease of use and usefulness. Perceived data privacy was discovered to positively impact attitude, perceived trust, perceived usefulness, perceived ease of use as well as behavioural intentions. The perceived trust mediated perceived data privacy on the attitudes in this study. Additionally, the two major variables in the proposed model - perceived trust and data privacy- affect attitudes of AVs significantly, with total effects being 0.637 and 0.604, respectively. Attitude is the most significant variable that correlates with behavioural intentions, which leads to acceptance of fully AVs. Multigroup analysis showed the gender, age and income related differences regarding the public acceptance of AVs. Several theoretical and practical implications are discussed in this paper.

Language: en

Keywords

Driverless car; Intelligent Transportation System; Smart mobility; Transport policy; User behaviour