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@INPROCEEDINGS{held2011ci,
     author = {Held, Pascal and Kruse, Rudolf},
     editor = {Hoffmann, Frank and H{\"{u}}llermeier, Eyke},
      month = dec,
      title = {Estimation of hidden driver properties based on the driving behavior},
  booktitle = {Proceedings of 21. Workshop Computational Intelligence},
     series = {Schriftenreihe des Instituts f{\"{u}}r Angewandte Informatik / Automatisierungstechnik},
     number = {40},
       year = {2011},
      pages = {1-14},
  publisher = {Karlsruher Institut f{\"{u}}r Technologie},
       issn = {1614-5267},
       isbn = {978-3-86644-743-1},
        url = {http://uvka.ubka.uni-karlsruhe.de/shop/download/1000024372},
   abstract = {Given a better knowledge about the driver the car’s driver assistance systems
could be specifically adapted, potentially increasing the systems’ acceptance. Our
purpose is to estimate hidden driver properties underlying the driving behavior. We
used a linear combination of different quantities as basis of the similarity calculation.
With the aid of an evolutionary algorithm we determined these quantities as well
as their weights. In a study with 26 subjects three hidden target properties were
examined and estimated. We reached a correlation of approximately 0.7 between
the predicted values and given measurements. In order to exclude overfitting of the
model, an additional optimization was carried out using random values. In this case
only a considerably smaller correlation of 0.36 could be achieved. As a consequence
we observed that the basic assumption applies at least to the three examined target
properties. We conclude that an estimation based on driving behavior is possible.}
}