Road testing to validate the ADAS and autonomous algorithm is expensive and time-consuming. No one does all the testing on the road because of them. A proven way is to bring efficient testing to a 3D simulated environment. Some of the benefits are, but not limited to, cost reduction (no more prototypes), more time (the “shift left”), and increased test coverage (test corner cases). However, the simulation environment has one big challenge for the OEM and Tier 1’s – it’s not real. The vehicle dynamic is not realistic enough so some testing still needs to be repeated on the road. With challenging real-world scenarios, strict statutory guidelines, and to ensure occupant safety, modern automobiles need to be cognizant of the surrounding objects and activities and should act responsibly (sometimes autonomously) to prevent a mishap and ensure pedestrian, occupant, and vehicle safety. To ensure these capabilities of a vehicle, it is impossible to put the vehicle in a real physical environment considering the safety of operations and economics around it. This work is a sophisticated approach to designing and building real-world virtual operating environments, to highlight the significance of high-fidelity vehicle models in virtual vehicle testing, and to the design and testing of a vehicle’s collision prevention system. To build a digital twin, the tools need to be OpenX standards compliant to accurately model the road network, road surface, road maneuvers and so on. With all of those combined, hundreds of custom road safety scenarios were built and classified based on complexity. This work demonstrates how the ADAS and AD safety & comfort algorithms were tested in vehicle control system with confidence.