A more appropriate method to evaluate the passive safety of vehicles

Achmus, S.; Zobel, R.

Affiliations

Abstract

Evaluation of the passive safety of vehicles from accident data has been attempted by different institutions. Researchers try to distinguish the relative importance of different factors associated with accidents often by means of regression models. But the decisive problem in evaluating the passive safety of vehicles from accident data by regression models is the assumption of linearity. Till now all applied procedures combine the crash parameters linearly either to calculate the injury severity (linear regression) or to calculate the logit of the injury risk (logistic regression). These methods are not an appropriate tool for evaluating the passive safety of vehicles since the influence of the crash parameters is obviously not linear. An increase in the change of velocity from 10 kmlh to 40 kmlh has a different effect than an increase from 80 km/h to 110 km/h. Most of the crash parameters exhibit nonlinear behaviour but it gets "linearized" by the above mentioned linear regression models. Therefore, the influence of the crash variables is described wrongly and one gets falsified results for the evaluation of passive safety of vehicles.

To avoid the linearity of these models we introduce a nonlinear nonparametric additive model. Here the crash parameters are combined additively after an appropriate transformation on each variable: Y=c+f₁(x₁)+…+f_k(x_k) with Y being the injury severity, x₁,…,x_k the crash parameters, c the average injury severity calculated from the accident data and f₁,…,f_k the unknown functions which have to be estimated nonparametricaily from the data. Nonparametricaily means that we do not assume the functions to be polynoms or to have another a priori given structure. The estimated functions show the effect of each of the variables, i.e. the function f_j represents the effect of the parameter x_j. It can be seen within which ranges of the parameter the contribution to the injury severity increases or decreases and within which areas the contribution to the injury severity remains constant.

This new approach is shown by an example from a real world data base.

Cited Works (3)

Year	Entry
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Cited By (2)

Year	Entry
2001	Cameron M, Narayan S, Newstead S, Ernvall T, Laine V, Langwieder K. Comparative analysis of several vehicle safety rating systems. In: Proceedings of the 17th International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 4-7, 2001; Amsterdam, The Netherlands.
2003	Kreiss J-P, Zobel R, Busch S. Essential components of a statisticaly valid crashworthiness rating. In: Proceedings of the 18th International Technical Conference on the Enhanced Safety of Vehicles (ESV). May 19-22, 2003; Nagoya, Japan.