rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Validation and verification of automated driving systems
  name:
    name part: Watzenig, Daniel
    role:
      role term: editor.
  name:
    name part: Stolz, Michael
    role:
      role term: editor.
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2026
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xv, 241 pages) : illustrations (chiefly color).
  abstract: 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 Office…
  table of contents: 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.
  note: Daniel Watzenig, Michael Stolz, editors.
  subject:
    topic: Automated vehicles
  classification: TL152.8 .V35 2026
  classification: 629.2/046
  related item:
    title info:
      title: Sustainable mobility & energy
  identifier: 9783032132697 (electronic bk.)
  identifier: 303213269X
  identifier: 9783032132680
  identifier: 9783032132703
  identifier: 9783032132710
  location:
    physical location: POD
  record info:
    record content source: GW5XE
    record creation date: 260505
    record change date: 20260801173601.1
    record identifier: in00005789681
    language of cataloging:
      language term: eng