Sae J3016 As A Learning Device For The Driving Automation Community
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SAE J3016 as a Learning Device for the Driving Automation Community
It is the tenth anniversary of SAE International’s Surface Vehicle Recommended Practice effort SAE J3016 to establish a nomenclature standard for driving automation systems and levels of automation. While not exhaustive, this report covers motivation, initiation, and continued development of J3016 regarding driving automation systems, noting that J3016 evolved as a learning device that facilitated the evolution of driving automation systems. It initially worked by establishing common terminology for the technical learning in the field, but over time, J3016 expanded to recognize the human roles in driving automation systems, with later iterations considering broader transportation ecosystems, including fleet operations and remote assistance centers. SAE J3016 as a Learning Device for the Driving Automation Community: Technical, Socio-technical, and Systemic Learning emphasizes ongoing learning to integrate diverse insights about technical, social, and socio-technical challenges of driving automation systems. It also addresses briefly the struggle to accommodate hybrid visions of driving automation systems. It provides a brief history and describes how J3016 changed over time to reflect and support driving automation community learning as lessons for driving automation, whether focused on-road or off-road, concluding with a summary of driving automation challenges and tasks. 9781468608977 9781468608984 https://doi.org/10.4271/EPR2024029
The Challenges of Nextgen ADAS and ADS and Related Vehicle Safety Topics
Advanced driver assistance systems (ADAS) and automated driving systems (ADS) continue to expand into the market at a rapid pace. As improved (i.e., next generation) versions of these systems become available, they will continue to face many challenges in their implementation and benefits for safety and driving operations. The solution will involve many parties, including road safety professionals and researchers who see the potential in these systems but may have difficulties keeping up with them, and safety advocates who are calling for these systems to achieve higher levels of safety now. The Challenges of Next-gen ADAS and ADS and Related Vehicle Safety Topics explores these challenges that will fall on the National Highway Traffic Safety Administration (NHTSA) and automakers as they balance costs and benefits; establish reasonable regulations and standards; and determine how to improve, test, deliver, and use these systems successfully. Perhaps the most formidable challenge will be overcoming the expectation that ADAS—and especially ADS—will always work perfectly in every scenario. ISBN 9781468609301 ISBN 9781468609318 https://doi.org/10.4271/EPR2025003
AI in Clinical Medicine
Author: Michael F. Byrne
language: en
Publisher: John Wiley & Sons
Release Date: 2023-02-13
AI IN CLINICAL MEDICINE An essential overview of the application of artificial intelligence in clinical medicine AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future. Readers will find that this book: Describes where AI is currently being used to change practice, and provides successful cases of AI approaches in specific medical domains. Dives into the actual implementation of AI in the healthcare setting, and addresses reimbursement, workforce, and many other practical issues. Addresses some of the unique challenges associated with AI in clinical medicine including ethical issues, as well as regulatory and privacy concerns. Includes bulleted lists of learning objectives, key insights, clinical vignettes, brief examples of where AI is successfully deployed, and examples of potential problematic uses of AI and possible risks. From radiology, to pathology, dermatology, endoscopy, robotics, virtual reality, and more, AI in Clinical Medicine: A Practical Guide for Healthcare Professionals explores all recent state-of-the-art developments in the field. It is an essential resource for a general medical audience across all disciplines, from students to clinicians, academics to policy makers.