AI is rapidly becoming central to ADAS, automated driving and SDVs. As these systems grow more sophisticated, auto makers face increasing pressure to demonstrate that they operate safely, reliably and as intended throughout the vehicle lifecycle. Providing this assurance is a major challenge as the industry works to bring increasingly intelligent vehicles to market while meeting evolving regulatory and safety requirements.
Keysight Technologies and the Centre for Assuring Autonomy (CfAA) at the University of York (UK) have announced a research collaboration to advance the safe deployment of artificial intelligence (AI) in software-defined vehicles (SDVs). The collaboration will focus on developing practical methods to validate AI systems and generate the evidence needed to demonstrate their safety and reliability. The work is designed to enable auto makers and suppliers to meet emerging industry requirements while reducing development risk and accelerating the deployment of AI-enabled automotive systems.
Keysight and the CfAA say that together they will help bridge the gap between AI safety research and practical engineering by advancing methodologies for structured AI safety cases and building justified confidence in the safety of AI-enabled automotive systems.
The research will focus on creating evidence-driven approaches to support the implementation of ISO/PAS 8800 requirements, exploring measurable safety-scoring methodologies grounded in academic research and industry standards, and designing practical frameworks for generating auditable AI safety evidence. The resulting methodologies are intended to support the process of building AI safety cases, improve confidence in AI validation, and help engineering teams demonstrate justified AI safety more efficiently throughout the product lifecycle.
By combining the university’s academic expertise with Keysight’s AI validation techniques, the collaboration seeks to advance methodologies applicable to automotive AI development.
Simon Burton, chair in systems safety at the University of York, said, “The automotive industry is at a pivotal point where AI technologies are becoming increasingly integral to vehicle functionality. Ensuring these systems can be evaluated using robust, evidence-based approaches is essential. This is where the CfAA is ideally placed to support Keysight. We have produced several freely accessible frameworks and guidance already being used by industry safety professionals in the transport sector. This collaboration is another way we are supporting the advancement of practice methods that help translate AI safety principles into engineering practices that can be applied in safety-critical environments.”
Lukas Klose, head of the automotive AI Solution Center at Keysight, added, “Automotive organizations need practical and scalable ways to build confidence in AI-enabled systems. By combining leading research in safety assurance with Keysight’s holistic AI Validation Framework, we aim to develop methodologies that help engineering teams generate structured evidence for AI safety cases and support the deployment of trustworthy AI technologies in conformance with international standards such as ISO/PAS 8800.”
The research is expected to inform future development of Keysight’s AI Software Integrity Builder, strengthening support for AI safety arguments, evidence generation and validation aligned with automotive industry expectations.
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