Abstract: This study examines the potential of Shared Autonomous Vehicle (SAV) systems in small and medium-sized urban areas through two analyses. The first evaluates the deployment of Shared Autonomous Electric Vehicles (SAEVs) across 374 U.S. urban areas using an agent-based simulation framework incorporating fleet operations, battery monitoring, and charging modules. Key performance indicators include fleet size, trips per vehicle, and charging infrastructure needs under Level 2 and Level 3 charging technologies. Results reveal significant spatial variation in system performance associated with road network structure and travel demand. Level 3 charging demonstrates higher operational efficiency, supporting more trips per vehicle and requiring fewer charging stations than Level 2 infrastructure. The second analysis focuses on short-distance trips, which represent a large share of travel in low-density areas yet are mostly completed by private vehicles. Using one month of connected vehicle trajectory data from Tuscaloosa, Alabama (114,821 trips), an agent-based simulation evaluates SAV systems with and without dynamic ridesharing (DRS). Results show that DRS significantly improves system efficiency, enabling vehicles to complete over three times more trips per vehicle while maintaining acceptable waiting and detour times. These findings highlight the importance of charging technology and ridesharing strategies in designing efficient SAV systems for smaller urban environments.