In the modern automotive industry, the testing of Advance Driver Assistance Systems (ADAS) and autonomous driving systems is of paramount importance for certification and validation. The complexity of these tests, aimed at validating system functionality, is evolving rapidly. This thesis is dedicated to the development of an enhanced and robust testing system that empowers highly automated testing in both proving ground and virtual environment, mainly focus on later one. The project presents a Robot Operating System (ROS2) communication framework for the scenario-based test system. Different traffic participants such as cars, pedestrians, maps, and traffic infrastructure are controlled via ROS2. ASAM OpenSCENARIO and its domain model is used to create a scenario comprised of different actors, actions and events, which are played using the Scenario Runner. To make the system more robust, a module for dynamic action translation into trajectory way points is developed and a communication interface to the Esmini, a lightweight simulation, tool is also developed. Furthermore, the developed scenario-based testing framework is demonstrated through example use case scenarios, such as lane changes and follow trajectory, to showcase its functionality and effectiveness. This setup allows for robust scenario-based testing for ADAS virtual validation, ensuring a comprehensive evaluation of real-world conditions and interactions.