Assessing public receptivity and preference formation in the transition to fully autonomous vehicles
Year: 2025
Type: article
Study design: Observational Study
Abstract: Fully autonomous vehicles (FAVs) are expected to reshape transportation systems and benefit society in several ways, but their advantages do not guarantee that the public will embrace them, a factor that is critical to their widespread deployment. This local pilot case study in Arlington, Texas (N = 295) aimed to supplement the existing literature on the adoption of autonomous vehicles (AVs) by investigating how the public’s perceptions shift as the level of autonomy increases. A survey questionnaire was developed to examine how demographic and attitudinal factors influence automation preference rankings and non-parametric statistical tests were used to evaluate the responses. The findings indicated significant variations in ranking preferences, with an overall preference for manual vehicles, followed by partially autonomous vehicles and FAVs. Among different demographic groups, age, gender, race, and prior exposure to AVs were found to be significant for ranking manual vehicles and FAVs. Spearman’s rank correlation analysis revealed a mirrored and opposite trend across attitudinal factors for rankings of manual vehicles and FAVs, but preferences for partial automation were not strongly influenced by them. This study highlights the importance of public receptivity to FAVs and may benefit policymakers by providing insight into the factors that affect the perceptions of prospective users, thereby facilitating their integration onto existing roadways. • The study explored how public perceptions shift as vehicular autonomy increases. • Autonomy levels play an important role in consumer adoption. • Familiarity and comfortability may contribute to preferences for manual vehicles. • Respondents express less resistance to adopting lower levels of autonomy. • Insight into the public’s comfort levels can guide successful FAV deployment.
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,540
OpenAlex ID: W4416759979