Autonomous systems exhibit failure modes in dynamic environments that lead to safety-critical accidents. Mitigating these risks ensures operational reliability and prevents catastrophic vehicle damage.

Inconsistent evaluation of automated driving functions leads to safety risks and unpredictable vehicle performance. Standardizing quality assessment ensures functional safety and aligns vehicle development with real-world human driving expectations.

Discrepancies between distributed data representations lead to unreliable autonomous vehicle function execution. Ensuring behavioral uniformity across decentralized nodes prevents unpredictable control failures.