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Title: Understanding public acceptance of autonomous vehicles using the theory of planned behaviour
Authors: Yuen, Kum Fai 
Chua, Grace
Wang, Xueqin
Ma, Fei
Li, Kevin X.
Keywords: Engineering::Civil engineering
Issue Date: 2020
Source: Yuen, K. F., Chua, G., Wang, X., Ma, F. & Li, K. X. (2020). Understanding public acceptance of autonomous vehicles using the theory of planned behaviour. International Journal of Environmental Research and Public Health, 17(12), 4419-.
Journal: International Journal of Environmental Research and Public Health
Abstract: Public acceptance of autonomous vehicles (AVs) is vital for a society to reap their intended benefits such as reduced traffic accidents, land usage, congestion and environmental pollution. The purpose of this paper is to use the theory of planned behaviour to pinpoint and examine the components affecting public acceptance of AVs. A model consisting of a network of hypothesised relationships is introduced. Thereafter, 526 residents in Seoul, Korea, were given a survey created for this research. Subsequently, to evaluate the collected information and estimate the model, structural equation modelling was adopted. The outcomes show individuals' mindset on AVs, subjective customs, and behavioural influence directly influencing the acceptance of AVs. Furthermore, cognitive and emotive factors, namely comparative advantage, compatibility, complexity and hedonic motivation indirectly influence the acceptance of AVs via mindset and behavioural manipulation. Based on analysing the cumulative effect, attitude emerged with the strongest effect on public acceptance of autonomous vehicles. After this is, in decreasing order of influence, behavioural control, relative advantage, subjective norms, compatibility, hedonic motivation and complexity. The findings of this study implicate the prioritisation and allocation of resources, and policies relating to marketing, education, subsidisation and infrastructure development to better public acceptance of AVs.
ISSN: 1661-7827
DOI: 10.3390/ijerph17124419
Rights: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

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