Journal of Real-Time Image Processing

, Volume 11, Issue 1, pp 179–191 | Cite as

Real-time lane tracking using Rao-Blackwellized particle filter

  • Marcos NietoEmail author
  • Andoni Cortés
  • Oihana Otaegui
  • Jon Arróspide
  • Luis Salgado
Original Research Paper


A novel approach to real-time lane modeling using a single camera is proposed. The proposed method is based on an efficient design and implementation of a particle filter which applies the concepts of the Rao-Blackwellized particle filter (RBPF) by separating the state into linear and non-linear parts. As a result the dimensionality of the problem is reduced, which allows the system to perform in real-time in embedded systems. The method is used to determine the position of the vehicle inside its own lane and the curvature of the road ahead to enhance the performance of advanced driver assistance systems. The effectiveness of the method has been demonstrated implementing a prototype and testing its performance empirically on road sequences with different illumination conditions (day and nightime), pavement types, traffic density, etc. Results show that our proposal is capable of accurately determining if the vehicle is approaching the lane markings (Lane Departure Warning), and the curvature of the road ahead, achieving processing times below 2 ms per frame for laptop CPUs, and 12 ms for embedded CPUs.


Kalman Filter Particle Filter Lane Change Obstacle Detection Embed Processor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work has been partially supported by the program ETORGAI 2011-2013 of the Basque Government under project IEB11. This work has been possible thanks to the cooperation with Datik–Irizar Group for their support in the installation, integration and testing stages of the project.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marcos Nieto
    • 1
    Email author
  • Andoni Cortés
    • 1
  • Oihana Otaegui
    • 1
  • Jon Arróspide
    • 2
  • Luis Salgado
    • 2
  1. 1.Vicomtech-ik4Donostia–San SebastiánSpain
  2. 2.Grupo de Tratamiento de ImágenesUniversidad Politécnica de MadridMadridSpain

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