• DocumentCode
    1517980
  • Title

    Highly Automated Driving on Freeways in Real Traffic Using a Probabilistic Framework

  • Author

    Ardelt, Michael ; Coester, Constantin ; Kaempchen, Nico

  • Author_Institution
    BMW Group Res. & Technol., Munich, Germany
  • Volume
    13
  • Issue
    4
  • fYear
    2012
  • Firstpage
    1576
  • Lastpage
    1585
  • Abstract
    A system, particularly a decision-making concept, that facilitates highly automated driving on freeways in real traffic is presented. The system is capable of conducting fully automated lane change (LC) maneuvers with no need for driver approval. Due to the application in real traffic, a robust functionality and the general safety of all traffic participants are among the main requirements. Regarding these requirements, the consideration of measurement uncertainties demonstrates a major challenge. For this reason, a fully integrated probabilistic concept is developed. By means of this approach, uncertainties are regarded in the entire process of determining driving maneuvers. While this also includes perception tasks, this contribution puts a focus on the driving strategy and the decision-making process for the execution of driving maneuvers. With this approach, the BMW Group Research and Technology managed to drive 100% automated in real traffic on the freeway A9 from Munich to Ingolstadt, showing a robust, comfortable, and safe driving behavior, even during multiple automated LC maneuvers.
  • Keywords
    decision making; driver information systems; probability; road safety; road traffic; BMW Group Research and Technology; Ingolstadt; LC maneuvers; Munich; automated lane change maneuvers; decision-making concept; driving strategy; freeways; highly automated driving; measurement uncertainty; perception tasks; probabilistic framework; real traffic; traffic participant general safety; traffic participant robust functionality; Decision making; Probabilistic logic; Robustness; Safety; Traffic control; Uncertainty; Advanced driver-assistance systems (ADASs); highly automated driving; lateral vehicle guidance; probabilistic decision making;
  • fLanguage
    English
  • Journal_Title
    Intelligent Transportation Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1524-9050
  • Type

    jour

  • DOI
    10.1109/TITS.2012.2196273
  • Filename
    6200871