Abstract

Objective: Assessment of the effectiveness of advanced driver assistance systems (ADAS) plays a crucial role in accident research. A common way to evaluate the effectiveness of new systems is to determine the potentials for injury severity reduction. Because injury risk functions describe the probability of an injury of a given severity conditional on a technical accident severity (closing speed, delta V, barrier equivalent speed, etc.), they are predestined for such evaluations.Methods: Recent work has stated an approach on how to model the pedestrian injury risk in pedestrian-to–passenger car accidents as a family of functions. This approach gave explicit and easily interpretable formulae for the injury risk conditional on the closing speed of the car. These results are extended to injury risk functions for pedestrian body regions. Starting with a double-checked German In-depth Accident Study (GIDAS) pedestrian-to-car accident data set (N = 444) and a functional–anatomical definition of the body regions, investigations on the influence of specific body regions on the overall injury severity will be presented. As the measure of injury severity, the ISSx, a rescaled version of the well-known Injury Severity Score (ISS), was used. Though traditional ISS is computed by summation of the squares of the 3 most severe injured body regions, ISSx is computed by the summation of the exponentials of the Abbreviated Injury Scale (AIS) severities of the 3 most severely injured body regions. The exponentials used are scaled to fit the ISS range of values between 0 and 75.Results: Three body regions (head/face/neck, thorax, hip/legs) clearly dominated abdominal and upper extremity injuries; that is, the latter 2 body regions had no influence at all on the overall injury risk over the range of technical accident severities. Thus, the ISSx is well described by use of the injury codes from the same body regions for any pedestrian injury severity. As a mathematical consequence, the ISSx becomes explicitly decomposable into the 3 body regions and so are the risk functions as body region–specific risk functions. The risk functions for each body region are stated explicitly for different injury severity levels and compared to the real-world accident data.Conclusions: The body region–specific risk functions can then be used to model the effect of improved passive safety systems. These modified body region–specific injury risk functions are aggregated to a new pedestrian injury risk function. Passive safety systems can therefore be modeled in injury risk functions for the first time.A short example on how the results can be used for assessing the effectiveness of new driver assistance systems concludes the article.

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