http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Validation and verification of automated driving systems
1 online resource (xv, 241 pages) : illustrations (chiefly color).
This book offers a comprehensive overview on the state-of the art methods in validation and verification of automated driving systems. It covers latest development in corresponding standards (ASAM), discusses challenges and offers insights in proposed frameworks and tooling to address those. The content Challenges and Approaches in the Validation of CCAM - Standards: The language enabling cooperation in CCAM V&V - Validation of Perception Sensor Models - Challenges and Solutions - Novel Classification Scheme for Perception Sensors Incorporated into Simulation Validation Process for AD - Safety assurance of AI-enabled sensing and perception subsystem used in autonomous vehicles - Scenario-Based Safety Assessment of Automated Driving Systems - Credible Safety Validation Toolchain for Automated Driving Functions The editors Michael Stolz received the M.Sc. degree in mechanical engineering (2002) and the PhD. degree in electrical engineering (2013) from Graz University of Technology, Graz, Austria. He was in the automotive industry as a development engineer for ten years (one year as the skill team leader in the field of automated driving).He was a part of the Automated Driving Research Team with the Institute of Automation and Control, Graz University of Technology, as a postdoctoral project assistant and is now with the Institute of Computer Graphics and Vision at Graz University of Technology. He is also within Virtual Vehicle Research GmbH as a key researcher responsible for project planning and technical guidance of funded projects in the field of automated driving and artificial intelligence. Daniel Watzenig holds a doctorate in electrical engineering. He received the venia docendi (habilitation) in electrical measurement science and signal processing from Graz University of Technology, Austria, where he was appointed Full Professor of Multi-Sensor Perception of Autonomous Systems at the Institute of Visual Computing. He currently serves as Chief Technology Officer (CTO) and Head of the Electronics Systems and Software Department at Virtual Vehicle Research GmbH. He has been a guest lecturer at Stanford University, USA and Tongji University, China for several years. He is the founder of the Autonomous Racing Graz Team and, since 2024, has served as Vice Chair and Executive Committee Member of the IEEE Austria Section. He is also an IEEE Distinguished Lecturer in the field of autonomous vehicles, a Board Member of the INSIDE Industry Association (European Initiative on Intelligent Digital Systems), and a Member of the Academic Advisory Council of PAVE (Partners for Automated Vehicle Education). The book series Sustainable Mobility and Energy highlights the crucial role of sustainable mobility in reducing CO2 emissions. This series features insights from leading experts on electric and fuel cell vehicles, which offer eco-friendly alternatives to conventional engines, especially when powered by renewable energy sources. Utilizing clean energy significantly reduces air pollution and dependence on fossil fuels. Additionally, the integration of modern communication technology enhances traffic control, reduces congestion, and increases road safety. Join us in exploring innovative solutions for a greener and more efficient future.
Challenges and Approaches in the Validation of CCAM -- Standards: The language enabling cooperation in CCAM V&V -- Validation of Perception Sensor Models - Challenges and Solutions -- Novel Classification Scheme for Perception Sensors Incorporated into Simulation Validation Process for AD -- Safety assurance of AI-enabled sensing and perception subsystem used in autonomous vehicles -- Scenario-Based Safety Assessment of Automated Driving Systems -- Credible Safety Validation Toolchain for Automated Driving Functions.
Daniel Watzenig, Michael Stolz, editors.