• DocumentCode
    2981283
  • Title

    Rule-based tracking of multiple lanes using particle filters

  • Author

    Vacek, Stefan ; Bergmann, Stephan ; Mohr, Ulrich ; Dillmann, Rüdiger

  • Author_Institution
    Inst. of Comput. Sci. & Eng., Karlsruhe Univ.
  • fYear
    2006
  • fDate
    Sept. 2006
  • Firstpage
    203
  • Lastpage
    208
  • Abstract
    Tracking of lanes is essential for intelligent vehicles in order to drive autonomously. A system is presented which allows tracking of multiple lanes. The system is based on a clear modelling of a lane and the parameter set of each lane is estimated using a particle filter which fuses different cues. A finite-state machine then decides whether or not a lane is really tracked. For each lane, a separate tracker is used and a set of rules controls the life-cycle of all trackers and keeps track of all the estimated lanes
  • Keywords
    finite state machines; intelligent robots; particle filtering (numerical methods); remotely operated vehicles; tracking; finite-state machine; intelligent vehicles; multiple lanes; particle filters; rule-based tracking; Fuses; Intelligent systems; Intelligent vehicles; Knowledge based systems; Life estimation; Particle filters; Particle tracking; Probability density function; Roads; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multisensor Fusion and Integration for Intelligent Systems, 2006 IEEE International Conference on
  • Conference_Location
    Heidelberg
  • Print_ISBN
    1-4244-0566-1
  • Electronic_ISBN
    1-4244-0567-X
  • Type

    conf

  • DOI
    10.1109/MFI.2006.265649
  • Filename
    4042066