A Flexible Architecture for Driver Assistance Systems

  • Uwe Handmann
  • Iris Leefken
  • Christos Tzomakas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1701)


The problems encountered in building a driver assistance system are numerous. The collection of information about real environment by sensors is erroneous and incomplete. When the sensors are mounted on a moving observer it is difficult to find out whether a detected motion was caused by ego-motion or by an independent object moving. The collected data can be analyzed by several algorithms with different features designed for different tasks. To gain the demanded information their results have to be integrated and interpreted. In order to achieve an increase in reliability of information a stabilization over time and knowledge about important features have to be applied. Different solutions for driver assistance systems have been published. An approach proposed by Rossi et al. [8] showed an application for a security system. An application being tested on highways has been presented by Bertozzi and Broggi [1]. Dickmanns et al. presented a driving assistance system based on a 4D-approach [2]. Those systems were mainly designed for highway scenarios, while the architecture presented by Franke and Görzig [3] has been tested in urban environment.


Behavior Planning External Knowledge Intelligent Vehicle Lane Detection Dynamic Knowledge 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Uwe Handmann
    • 1
  • Iris Leefken
    • 1
  • Christos Tzomakas
    • 1
  1. 1.Institut für NeuroinformatikRuhr Universität BochumBochum

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