Driver Perceptions of V2V and V2I for Autonomous Vehicles: A Study of Technology Acceptance Factors

Abstract

This study will examine user acceptance towards the latest autonomous vehicle technologies with a focus on vehicle-to-vehicle (V2V) and vehicle-to infrastructure (V2I) technologies. An online survey was utilised to collect 203 responses (from a diverse group of people with about 35 master students). This research will predominantly utilise a quantitative research approach to study consumer views on autonomous vehicle technologies and will be conducted amongst professional and nonprofessional drivers. The technology acceptance model (TAM) by Davis represents the underlying research model of this study updated to include significant factors. Hypothesis testing is performed for three scenarios (AV, V2V, and V2I) using multiple regression analysis and ANOVA test in SPSS version 20. However, the outcomes of this study revealed that V2V exhibited the most considerable and statistically significant positive impact on the driver, as evidenced by the variables compatibility (COP) and perceived ease of use (PEOU). Besides, the study also conducted on V2I demonstrated that the most significant positive influence was observed by attitude towards using (ATU) and driver context (DC), which relates to the existing literature on pervasive computing. Furthermore, it was found that PEOU and DC variables exhibited a strong positive impact on autonomous vehicles (AV), with statistical significance.