An Empirical Study of V2V and V2I Regarding Technology Acceptance for Autonomous Vehicles

Abstract

Due to increasing innovation and improvement in technology, vehicle manufacturers have begun to devise major ways to improve capacity, reduce the possibility of delays and to adopt innovative technology. Transport fleets have increased dramatically, resulting in significant damage and accidents, placing lives at major risk and creating uncertainty. This has resulted in the onset of autonomous vehicle technology being created, such as vehicle-to-vehicle (V2V) and vehicle-to infrastructure (V2I) technologies. However, autonomous vehicles (AVs) are replete with problems referring to limitations in design, implementation, and practical applications. Moreover, the concept of this research is to explore the potential of V2V and V2I technologies to overcome the shortcoming of sensors such as cameras, radar, ultrasonic and LiDAR against adverse driving conditions. This study will examine user acceptance towards the latest autonomous vehicle technologies with a focus on V2V and V2I. 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.