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Despite the growing interest in implementing shared autonomous vehicles (SAVs) as a new mobility mode, there is still a lack of methodologies to unpack SAV adoption by individuals after experiencing self-driving vehicles. This study aimed to fill this gap by analyzing data collected from a users’ survey of a self-driving shuttle piloted downtown and on a university campus in Arlington, TX. Employing structural equation modeling, the hypothesized relationships between SAV adoption and key factors were tested. Data analyses indicated that individuals with limited access to a private vehicles, low-income people, young adults, university students, males, and Asians were more likely to ride this new service. Furthermore, results showed that SAV service attributes, including internal and external service performance and usual transportation mode, affected users’ willingness to continue using the service in the future. The …