High Level Sensor Data Fusion of Radar and Lidar for Car-Following on Highways

  • Michael Schnürmacher
  • Daniel Göhring
  • Miao Wang
  • Tinosch Ganjineh
Part of the Studies in Computational Intelligence book series (SCI, volume 480)


We present a real-time algorithm which enables an autonomous car to comfortably follow other cars at various speeds while keeping a safe distance. We focus on highway scenarios. A velocity and distance regulation approach is presented that depends on the position as well as the velocity of the followed car. Radar sensors provide reliable information on straight lanes, but fail in curves due to their restricted field of view. On the other hand, lidar sensors are able to cover the regions of interest in almost all situations, but do not provide precise speed information. We combine the advantages of both sensors with a sensor fusion approach in order to provide permanent and precise spatial and dynamical data. Our results in highway experiments with real traffic will be described in detail.


Data Fusion Lidar Data Radar Sensor Fusion Module Lidar Sensor 
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.



The authors wish to thank the German federal ministry of education and research (BMBF).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Michael Schnürmacher
    • 1
  • Daniel Göhring
    • 1
  • Miao Wang
    • 1
  • Tinosch Ganjineh
    • 1
  1. 1.Freie Universität BerlinInstitut für InformatikBerlinGermany

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