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Fundamentals of Design of Experiments for Automotive Engineering Volume I

In a world where innovation and sustainability are paramount, Fundamentals of Design of Experiments for Automotive Engineering: Volume I serves as a definitive guide to harnessing the power of statistical thinking in product development. As first of four volumes in SAE International’s DOE for Product Reliability Growth series, this book presents a practical, application-focused approach by emphasizing DOE as a dynamic tool for automotive engineers. It showcases real-world examples, demonstrating how process improvements and system optimizations can significantly enhance product reliability. The author, Young Chiang, leverages extensive product development expertise to present a comprehensive process that ensures product performance and reliability throughout its entire lifecycle. Whether individuals are involved in research, design, testing, manufacturing, or marketing, this essential reference equips them with the skills needed to excel in their respective roles.
Best Practice

AVSC Best Practice for ADS Remote Assistance Use Case

Automated driving system-dedicated vehicles (ADS-DVs) can handle a wide variety of circumstances they might encounter on the road. When circumstances are encountered that exceed ADS design capabilities, the ADS is designed to bring the vehicle into a minimal risk condition (MRC). When an ADS-DV encounters these conditions—identified as “triggers” within this best practice—they can request remote assistance (RA) from a remotely located human operator. RA involves the provision of guidance, suggestions, or recommendations to a vehicle from a remote location, without direct control of the vehicle. RA has emerged as a useful tool in supporting the operation of an ADS. It can complement the capabilities of ADS-DVs and improve overall system performance and utilization, particularly in situations that exceed ADS design capabilities. This best practice provides guidelines for integrating remote assistance within the context of ADS.