Machine Learning for safety-critical automotive functions

Would you like to use machine learning (ML) without compromising the safety of vehicle functions?

Our training course "Machine Learning for safety-critical automotive functions" covers the fundamental principles of arguing the safety of automotive functions that make use of machine learning technologies. In particular, we focus on the practical application of the ISO 21448 and ISO PAS 8800 standards.

In our training, we show you tailored methods and tools for integrating machine learning into your project without risking the reliability and safety of the application. We take into account existing and future standards for artificial intelligence (AI), safety, and standards from the automotive industry. With the acquired knowledge you will be able to develop and evaluate ML-based safety-related functions.

Learning content

The course includes the following topics and can be adapted to your use case and requirements:

• Introduction to machine learning on the basis of an example function and publicly available data
• Safety challenges of machine learning
• Short introduction to relevant safety standards and their impact on machine learning
• Safety lifecycle for machine learning functions
• Derivation of safety requirements for ML functions with particular focus on the definition of safety-related properties such as accuracy, robustness, prediction certainty, transparency and explainability
• The impact of training and test data on safety
• Methods for evaluating the performance of the ML function against its safety requirements
• Safety analysis applied to machine learning
• Architectural measures to improve the safety of ML functions
• Design-time and operation time methods for ensuring the safety of ML functions
• Assurance arguments for machine learning

Target audience

The course is designed for developers who want to integrate machine learning into their automotive functions and must provide the corresponding safety verification. The focus is on people who need to evaluate and ensure the safety of ML-based functions and systems. The curriculum offers a structured framework and a comprehensive toolkit for the safe use of ML in changing and complex scenarios.

Prerequisites

Participants should have experience with applying automotive standards and a basic understanding of safety techniques. Prior ML knowledge is beneficial but not mandatory.