| AI-driven in-cabin simulation enables scalable validation of Driver and Occupant Monitoring Systems (DMS/OMS), which must operate reliably across diverse users, behaviors, sensors, and environments. Traditional vehicle-based testing cannot efficiently cover this complexity. This presentation introduces a simulation-centric approach combining physics-based modeling, high-fidelity digital humans, and precise virtual sensors, augmented selectively with AI. Rather than relying on end-to-end generative AI, controlled AI methods extend motion capture, create systematic variations, and cover rare safety-critical scenarios. The approach delivers reproducible ground truth, consistent sensor outputs, and scalable validation for camera, IR, and multimodal systems. Applications include algorithm validation, sensor placement studies, synthetic-to-real training, and structured Euro NCAP-relevant testing. |
By engineers, for engineers: A technically grounded guide to the rapidly evolving in-cabin technology industry and companies.
