The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

Abstract

Excessive dependence on autonomous vehicles (AVs) may exacerbate traffic congestion and increase exhaust emissions in the future. The diffusion of AVs may be significantly affected by the public’s acceptance. A few factors that may affect people’s acceptance of AVs have been researched in the existing studies, one-third of which cited behavioral theories, while the rest did not. A total of seven factors with behavior theories are screened out that significantly affect the acceptance intention, including perceived ease of use, attitude, social norm, trust, perceived usefulness, perceived risk, and compatibility. Six factors without behavior theories are summed up that affect AV acceptance, namely safety, performance-to-price value, mobility, value of travel time, symbolic value, and environmentally friendly. We found that people in Europe and Asia have substantial differences in attitudes toward AVs and that safety is one of the most concerned factors of AVs by scholars and respondents. Public acceptance of the different types of AVs and consumers’ dynamic preferences for AVs are highlighted in the review too. The quality of literature is systematically assessed based on previously established instruments and tailored for the current review. The results of the assessment show potential opportunities for future research, such as the citation of behavior theories and access to longitudinal data. Additionally, the experimental methods and the utilization of mathematical and theoretical methods could be optimized.

How different autonomous vehicle presentation influences its acceptance: Is a communal car better than agentic one?

“…Interestingly, in the case of level 3 AVs, it was reported that it was the ease of use which predicted the intention to use and not perceived usefulness [30]. All in all, it was the perceived usefulness which had most often the strongest influence on intention to use AVs [40].…”

“…Authors of AV's acceptance models often adapt the original models and incorporate novel factors. Among the most cited factors were respectively: perceived ease of use, perceived usefulness, trust, attitude, social norm, perceived risk and compatibility [40]. Such research is recently rapidly gaining in numbers (e.g.…”

“…As mentioned, TAM is the most cited behavior theory in AV acceptance research [40]. It was developed by Davis [41] to predict information technology acceptance.…”

“…Moreover, such factors like higher income [ 35 ], living in an urban area [ 38 ], tech-savvy and also involvement in more crashes [ 39 ] positively affect the attitudes towards AVs [ 13 ]. A meta-analysis of studies not based on behavior theories showed that the acceptance of AVs was explained by safety, performance-to-price value, mobility, travel time, symbolic value, and environmental friendliness [ 40 ]. The role of legal liability and regulation issues of AVs was also confirmed [ 26 ].…”

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“…However, the responses of the survey that follows support this notion of hesitance and the hybrid option of human-machine collaboration is currently a more acceptable choice. By training the AI system and updating the road network with the required infrastructure, fully autonomous versions could be required in the near future and will be further investigated [31].…”