Looking to enable automakers and suppliers to meet emerging industry requirements while reducing development risk and accelerating the deployment of artificial intelligence (AI-)enabled automotive systems, 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 AI in software-defined vehicles (SDVs).
Keysight and the CfAA noted that AI has rapidly become a core technology in advanced driver assistance systems (ADAS), automated driving functions and SDVs. As these capabilities become more sophisticated, automotive organisations face growing pressure to demonstrate that AI systems operate safely, reliably and as intended, not only during development but throughout the vehicle lifecycle. Keysight and CfAA stressed that providing that proof is one of the industry’s most significant challenges, as automakers work to bring increasingly intelligent vehicles to market while meeting evolving regulatory and safety expectations.
The University of York has a legacy in research in safety engineering and the assurance of complex systems across domains, including transport and automotive. By combining the university’s academic expertise with Keysight’s AI validation techniques, the collaboration seeks to advance methodologies applicable to automotive AI development.
In addition, Keysight and the CfAA said that they will focus on developing practical methods for validating AI systems and generating the evidence needed to demonstrate their safety and reliability. By working together, they assured that they will help to 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.
In deeper technical terms, the research will focus on the creation of 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 creating practical frameworks for generating auditable AI safety evidence.
The two organisations said 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.
The research is also expected to inform future development of Keysight’s AI Software Integrity Builder, enable enhanced support for AI safety arguments and safety evidence generation, and offer validation activities aligned with automotive industry expectations.
“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,” said Simon Burton, chair in systems safety at the University of York.
“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 centre at Keysight, added: “Automotive organisations 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.”
