Statistical Behavior Modeling for Driver-Adaptive Precrash Systems
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...
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Published in | IEEE transactions on intelligent transportation systems Vol. 14; no. 4; pp. 1764 - 1772 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
IEEE
01.12.2013
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Subjects | |
Online Access | Get full text |
ISSN | 1524-9050 1558-0016 |
DOI | 10.1109/TITS.2013.2267799 |
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Summary: | 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. |
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ISSN: | 1524-9050 1558-0016 |
DOI: | 10.1109/TITS.2013.2267799 |