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Although multiple studies have modeled and predicted the potential effects of shared autonomous vehicles (SAVs), the research on the adoption of SAVs by riders with actual ridership experience is still limited. In addition, the increasing tendency towards operating SAV technology requires understanding its efficiency while integrating it into the existing transportation network infrastructure. This study aims to identify the factors affecting the user's willingness to ride the SAVs based on the data collected from a comprehensive survey distributed among users and non-users of a self-driving pilot project called RAPID (Rideshare, Automation, and Payment Integration Demonstration) in Arlington, Texas. Using structural equation modeling (SEM), we identify the effects from vehicle ownership, RAPID usage, existing modes of transportation, RAPID service attributes (comfort and safety), and sociodemographic variables on …