Abstract
Autonomous Vehicles (AVs) are expected to improve various aspects of the transportation sector by reducing emissions, fuel consumption, traffic congestion, and human error. Their widespread adoption is highly dependent on public acceptance, however, and while the topic of AVs is receiving ever-increasing attention in the literature, few studies have delved into the determinants of the public’s receptivity towards Fully Autonomous Vehicles (FAVs). This study aims to fill that gap by providing an understanding of the factors that make FAVs both attractive and unattractive to prospective users. To achieve this goal, we designed a survey questionnaire informed by the unified theory of acceptance and use of technology to explore the attitudes and perceptions of the participants toward AVs and, more specifically, FAVs, and identify the main factors that drive those feelings and impressions. The questionnaire was distributed online to residents in Arlington, Texas, and an exploratory factor analysis was employed to evaluate the 295 survey responses. The results showed a range of attitudinal and behavioral variables that describe the psychological and social determinants of receptivity to FAVs, but the four main factors were shown to be: primary acceptance FAVs, anxiety about FAVs, driving enjoyment, and intrinsic trust in AVs. The findings of this study will provide insight into the barriers to FAV adoption and support policymakers and manufacturers who strive to ensure a smooth transition from partially autonomous to fully autonomous vehicles.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 696-703 |
| Number of pages | 8 |
| Journal | Transportation Research Procedia |
| Volume | 91 |
| DOIs | |
| State | Published - 2025 |
| Event | International Conference on The Science and Development of Transport, TRANSCODE 2025 - Zagreb, Croatia Duration: Dec 11 2025 → Dec 12 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
All Science Journal Classification (ASJC) codes
- Transportation
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