@article{MuehlfeldDoricErtlmeieretal., author = {M{\"u}hlfeld, Florian and Doric, Igor and Ertlmeier, Rudolf and Brandmeier, Thomas}, title = {Statistical Behavior Modeling for Driver-Adaptive Precrash Systems}, series = {IEEE Transactions on Intelligent Transportation Systems}, volume = {14}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {4}, publisher = {IEEE}, doi = {10.1109/TITS.2013.2267799}, pages = {1764 -- 1772}, abstract = {Precrash systems have the potential for preventing or mitigating the results of an accident. However, optimal precrash activation can be only achieved by a driver-individual parameterization of the activation function. In this paper, an adaptation model is proposed, which calculates a driver-adapted activation threshold for the considered precrash algorithm. The model analyzes past situations to calculate a driver-individual activation threshold that achieves a desired activation frequency. The advantage of the proposed model is that the distribution is estimated using a distribution model. This has the result that an activation threshold can be already determined using a small data set. In addition, the confidence interval that has to be considered is decreased. The proposed model was applied in a study with test subjects. Results of this paper confirm the usability of the model. In comparison with an empirical approach, the proposed model achieves a significantly lower threshold and, thus, a higher safety effect of the system.}, language = {en} }