Navigating the Evolving Landscape of Safety Standards for Machine Learning-based Road Vehicle Functions

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Navigating the Evolving Landscape of Safety Standards for Machine Learning-based Road Vehicle Functions is written by Simon Burton and published by SAE International. It's available with International Standard Book Number or ISBN identification 1468608371 (ISBN 10) and 9781468608373 (ISBN 13).

ML approaches to solving some of the key perception and decision challenges in automated vehicle functions are maturing at an incredible rate. However, the setbacks experienced during initial attempts at widespread deployment have highlighted the need for a careful consideration of safety during the development and deployment of these functions. To better control the risk associated with this storm of complex functionality, open operating environments, and cutting-edge technology, there is a need for industry consensus on best practices for achieving an acceptable level of safety. Navigating the Evolving Landscape of Safety Standards for Machine Learning-based Road Vehicle Functions provides an overview of standards relevant to the safety of ML-based vehicle functions and serves as guidance for technology providers—including those new to the automotive sector—on how to interpret the evolving standardization landscape. The report also contains practical guidance, along with an example from the perspective of a developer of an ML-based perception function on how to interpret the requirements of these standards. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2024017