As Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) grow in complexity, automotive companies must move faster without compromising safety or regulatory compliance. Virtual Twins of system, hardware, and software architectures enable engineers to model vehicles, sensors, and driving environments, supporting large-scale simulation and validation across thousands of scenarios well before physical testing. At the same time, AI-driven engineering is transforming ADAS development by automating requirements and scenario generation, analyzing massive datasets, and uncovering critical edge cases. By combining Virtual Twins with AI, organizations can expand validation coverage, streamline collaboration across disciplines, and significantly reduce development cycles, while improving system reliability, safety, and time to market.

• Master AD/ADAS complexity with Virtual Twins Use system, hardware, and software architectures to enable modeling, simulation, and large-scale virtual validation.
• Apply AI to transform ADAS engineering Automate requirements, test cases, and scenario generation while leveraging data to identify critical edge cases
• Combine AI and Virtual Twins to accelerate development Reduce development cycles, improve cross-team collaboration, and bring safer systems to market faster.