Simulation based testing plays a major role in Autonomous Driver Assistance System (ADAS) where safety is of utmost importance. There are already simulation frameworks in the market to test ADAS functionalities; however, the existing frameworks are of specific deficiencies. The existing simulation frameworks do not include multiple sensor support for sensor fusion testing. The simulation frameworks supporting radar stimulation is capable of emulating limited number of objects. Furthermore, these simulation frameworks do not function in real-time. The aim of this master thesis is to address the observed deficiencies by designing a simulation framework containing Radar Scene Emulator (RSE) equipped with radar sensor, camera sensor, Real-Time PC (RTPC), yaw simulator, Global Navigation Satellite System (GNSS) simulator and CARLA simulator. Stimulation of Radar point cloud is achieved by implementing an interface between CARLA and RSE. The RSE used in the proposed solution is capable of emulating 512-point cloud objects in real-time. The simulation framework is designed to support EuroNCAP testing for AEB and FCW functionalities. The framework is implemented to be scalable with a possibility to accommodate EuroNCAP test scenarios for other functionalities. The RTPC controls the CARLA simulator thus making the simulation framework function in real-time. The framework supports various weather simulations to test the robustness of the sensor fusion algorithms. Finally, the components of the simulation are evaluated to determine its precision. GNSS receiver emulates the coordinates from CARLA which proves the effective synchronicity between CARLA and GNSS receiver. The data integrity is maintained between CARLA and yaw simulator. A deviation of 0.83% has been observed while validating the synchronicity between CARLA and RTPC.