1 Scope
This document applies to safety-related systems that include one or more electrical
and/or electronic (E/E) systems that use AI technology and that is installed in series
production road vehicles, excluding mopeds. It does not address unique E/E systems
in special vehicles, such as E/E systems designed for drivers with disabilities.
This document addresses the risk of undesired safety-related behaviour at the vehicle
level due to output insufficiencies, systematic errors and random hardware errors
of AI elements within the vehicle. This includes interactions with AI elements that
are not part of the vehicle itself but that can have a direct or indirect impact on
vehicle safety.
EXAMPLE 1
Examples of AI elements within the vehicle include the trained AI model and AI system.
EXAMPLE 2
Direct impact on safety can be due to object detection by elements external to the
vehicle.
EXAMPLE 3
Indirect impact on safety can be due to field monitoring by elements external to the
vehicle.
The development of AI elements that are not part of the vehicle is not within the
scope of this document. These elements can conform to domain-specific safety guidance.
This document can be used as a reference where such domain-specific guidance does
not exist.
This document describes safety-related properties of AI systems that can be used to
construct a convincing safety assurance claim for the absence of unreasonable risk.
This document does not provide specific guidelines for software tools that use AI
methods.
This document focuses primarily on a subclass of AI methods defined as machine learning
(ML). Although it covers the principles of established and well-understood classes
of ML, it does not focus on the details of any specific AI methods e.g. deep neural
networks.