Relying solely on public road mileage accumulation to identify and validate against unknown-unsafe conditions is a statistical and logistical impossibility. This presentation outlines PlusAI’s systems and safety engineering framework, explicitly tailored to overcome the "Validation Mileage Fallacy" for Level 4 autonomous trucking deployments globally. By decoupling execution spaces into distinct problem, solution, verification, and validation layers, this architecture ensures that engineering overhead converges toward zero as new commercial missions are expanded. We will demonstrate how to systematically orchestrate scenario-driven decomposition, event re-play, and multi-tier Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) test environments. Furthermore, you will discover how machine learning style transfer is deployed to synthetically expand real-world datasets across challenging Operational Design Domain (ODD) conditions like rain, fog, night, and snow. Join us to explore a data-driven framework that unites ISO 15288, SOTIF, and layered safety cases with high-impact commercial scale.

• Why real-world road mileage alone cannot satisfy L4 safety case requirements.
• Methods to tailor ISO 15288 and SOTIF frameworks for scalable autonomous operations.
• How to systematically apply SiL, HiL, and closed-course test environments for verification
• Expanding ML data coverage synthetically from real events via weather style transfer.
• Aligning non-negotiable safety cases with technical compliance and commercial business goals.