Exploring motivating factors and constraints of using and adoption of shared autonomous vehicles (SAVs)

Self-driving vehicles are expected to reduce mobility barriers; however, it is still unclear how individuals will use them and how they will benefit the urban transportation system overall. This research aims to evaluate self-driving technology diffusion by applying and testing a conceptual model that was designed to unpack the possible determinants of the adoption of shared autonomous vehicles (SAVs). The study framework was developed based on the principles of socio-psychological theories of human behavior and investigates the adoption of SAVs by two groups of people: users and non-users. Structural equation modeling (SEM) was utilized to analyze the effects of motivational and restriction-related factors on SAV use and adoption, and the results indicated that perceived usefulness and restriction-related factors can positively motivate individuals to use SAVs more frequently. Ultimately, however, their adoption will depend on the public’ attitudes towards technology and as their perceptions of the inherent risks. This study provides new insights into the identification of potential SAV users and non-users and shows how their behavioral intentions differ.