CONTROL

Controlling Risk for Highly Automated Transportation Systems Operating in Complex Open Environments

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CONTROL takes highly automated driving to the next level, from restricted operational domains to automation in all situations. We research how to safely handle uncertainties such rain, poor visibility, and rare events. Environmental perception risks are detected in real time. The integrated system of sensors, data fusion, and intelligent decision‑making continuously adapts driving behavior, on both road and rail.

Dr. Cornel Klein

Project Coordinator, Siemens AG

Project

Safety Through Uncertainty Detection

Highly automated vehicles must operate and react reliably in complex, constantly changing environments, even when confronted with rare or unpredictable events. Defining and testing every single scenario would take decades. CONTROL takes a different approach: safety is created where uncertainties are detected, directly inside the vehicle.

INNOVATIONS

Making Uncertainties Measurable

The system continuously monitors how confidently it detects other road users and situations. It evaluates its own perception and estimates the probability that the detected information is correct. CONTROL develops methods for precise assessment across all levels of the perception chain, from sensing to data fusion to decision logic. Uncertainties are measured and integrated into the safety argumentation.

Demos

Practical Validation on Road and Rail

Whether in automotive or rail applications, the principles are the same. CONTROL uses shared metrics and tools across domains; differences only arise in how they are applied. The domains learn from one another and develop robust systems. The goal is to provide a solid foundation for safe decision‑making in critical situations. The project demonstrates this through realistic, practice‑oriented scenarios for both road and rail.