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.
Highlights
Autonomous vehicles (AVs) are self-driving vehicles capable of navigating roads, parking, sensing the environment and planning routes autonomously with minimum or without human conduction
This study proposes that public acceptance of AVs is affected by the attitude, subjective norms and behavioural control of individuals
As this paper evaluates the associations between latent constructs, structural equation modelling is adopted to study the obtained survey information
Summary
Autonomous vehicles (AVs) are self-driving vehicles capable of navigating roads, parking, sensing the environment and planning routes autonomously with minimum or without human conduction. From the users’ perspective, AVs are expected to improve safety by eliminating human errors caused by misjudgement, fatigue, impaired driving and environmental influences [3]. AVs are noted to improve users’ experience by providing more comfortable rides due to smoother braking and acceleration [4]. They free up users’ time which is originally dedicated to driving, allowing them to participate in other pertinent activities while commuting to their destination. AVs are noted to be more energy-efficient than convention vehicles. These decrease congestion, pollution and free up parking space for commercial
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