Road safety remains a critical global issue, as traffic accidents frequently occur, primarily due to human error. In response, Advanced Driver Assistance Systems (ADAS) have been developed to reduce accident risks. However, traditional validation methods, which rely on physical road tests, remain essential but are costly, time-consuming, and limited to a narrow range of use cases, failing to cover hazardous or particularly complex scenarios that, although occurring occasionally in the real world, are crucial for a complete and effective validation of monitoring systems. This thesis explores the application of virtual validation and synthetic data in testing automotive monitoring systems, with a focus on In-Cabin monitoring and Surround View camera systems.