Exploring Attitudes towards Fully Autonomous Vehicles: A Mixed Methods Approach

Engineering notes

Key topics: autonomous driving, autonomous vehicle, perception. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Autonomous vehicles (AVs) are expected to transform the transportation sector by reducing emissions, fuel consumption, congestion, and human error in the driving environment. However, the benefits of this emerging mobility option are highly dependent on public acceptance and widespread adoption. The adoption of AVs has gained increasing attention in the existing literature, but few studies have aimed to identify receptivity towards fully autonomous vehicles (FAVs), specifically in regions where shared AV pilot projects have been deployed. Therefore, this study intended to address this knowledge gap by illuminating prospective users’ acceptance of FAVs through the adoption of a mixed-methods approach. A survey questionnaire was designed and distributed online to residents of Arlington, Texas, to explore their attitudes towards FAVs. The analysis adopted a two-step approach to analyze the 295 valid responses, employing non-parametric tests to examine how attitudes are shaped by demographic characteristics and thematic analysis to analyze open-ended survey responses, capturing the breadth of public perceptions and attitudes. The quantitative analysis revealed significant attitudinal differences across demographic groups, with automation adoption approach and prior exposure to AVs having the most notable impact. The qualitative thematic analysis identified trust in AV technology, the integration of AVs into existing roadways, intentions to adopt FAVs, and institutional assurances as the four overarching themes. The results emphasize that FAV perceptions are not monolithic and instead are shaped by an interplay of demographic and attitudinal factors. Through an empirical analysis of individuals’ perceptions of FAVs, this study may benefit policymakers and manufacturers by facilitating a smooth transition from partially autonomous to FAVs.

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