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 inIEEE transactions on intelligent transportation systems Vol. 14; no. 4; pp. 1764 - 1772
Main Authors Muehlfeld, Florian, Doric, Igor, Ertlmeier, Rudolf, Brandmeier, Thomas
Format Journal Article
LanguageEnglish
Published IEEE 01.12.2013
Subjects
Adaptation models
Behavior modeling
driver adaptation
precrash activation
Road accidents
Road safety
Statistical analysis
Online AccessGet full text
ISSN1524-9050
1558-0016
DOI10.1109/TITS.2013.2267799

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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.
AbstractList 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.
Author Muehlfeld, Florian
Doric, Igor
Ertlmeier, Rudolf
Brandmeier, Thomas
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Snippet Precrash systems have the potential for preventing or mitigating the results of an accident. However, optimal precrash activation can be only achieved by a...
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SubjectTerms Adaptation models
Behavior modeling
driver adaptation
precrash activation
Road accidents
Road safety
Statistical analysis
Title Statistical Behavior Modeling for Driver-Adaptive Precrash Systems
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