With the rapid evolution of autonomous driving technology, how to efficiently and comprehensively validate and test its core algorithms has become a key concern across the industry. Traditional on-road testing is costly, time-consuming, and poses safety risks under complex or extreme conditions, making it difficult to cover potential long-tail scenarios in a timely manner. Therefore, establishing a closed-loop validation process that integrates Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and Real-World (RW) field testing is a crucial path to enhancing the reliability and engineering readiness of autonomous driving systems. This study proposes a contribution to this goal by building a full-stack Software-in-the-Loop testing and verification pipeline based on the open-source autonomous driving stack Autoware combined with the high-fidelity simulation platform CARLA.