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: Planning Universal On-Road Driving Strategies for Automated Vehicles
  name:
    name part: Heinrich, Steffen.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XV, 133 p. 59 illus., 25 illus. in color. online resource.
  abstract: Steffen Heinrich describes a motion planning system for automated vehicles. The planning method is universally applicable to on-road scenarios and does not depend on a high-level maneuver selection automation for driving strategy guidance. The author presents a planning framework using graphics processing units (GPUs) for task parallelization. A method is introduced that solely uses a small set of rules and heuristics to generate driving strategies. It was possible to show that GPUs serve as an excellent enabler for real-time applications of trajectory planning methods. Like humans, computer-controlled vehicles have to be fully aware of their surroundings. Therefore, a contribution that maximizes scene knowledge through smart vehicle positioning is evaluated. A post-processing method for stochastic trajectory validation supports the search for longer-term trajectories which take ego-motion uncertainty into account. Contents A Framework for Universal Driving Strategy Planning Sampling-Based Planning in Phase Space A Universal Approach for Driving Strategies Modeling Ego Motion Uncertainty Target Groups Scientists and students in the field of robotics, computer science, mechanical engineering Engineers in the field of vehicle automation, intelligent systems and robotics About the Author Steffen Heinrich has a strong background in robotics and artificial intelligence. Since 2009 he has been developing algorithms and software components for self-driving systems in research facilities and for automakers in Germany and the US.
  table of contents: A Framework for Universal Driving Strategy Planning -- Sampling-Based Planning in Phase Space -- A Universal Approach for Driving Strategies -- Modeling Ego Motion Uncertainty.
  note: by Steffen Heinrich.
  subject:
    topic: Robotics
  subject:
    topic: Automation
  subject:
    topic: Artificial intelligence
  subject:
    topic: Numerical analysis
  subject:
    topic: Robotics and Automation
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Numeric Computing
  classification: TJ210.2-211.495
  classification: T59.5
  classification: 629.892
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: AutoUni - Schriftenreihe, 119
  identifier: 9783658219543
  identifier: https://doi.org/10.1007/978-3-658-21954-3
  record info:
    record creation date: 180419
    record change date: 20191220130057.0
    record identifier: 978-3-658-21954-3