Citation

Vangi D, Gulino MS, Fiorentino A, Virga A. Proc. Inst. Mech. Eng. Pt. D J. Automobile Eng. 2019; 233(13): 3318-3326.

Copyright

(Copyright © 2019, Institution of Mechanical Engineers, Publisher SAGE Publishing)

DOI

10.1177/0954407018823658

PMID

unavailable

Abstract

The velocity change ΔV of a vehicle subject to a collision, widely recognized as an efficient crash severity indicator, is a typical 'a posteriori' parameter, not generally known until the crash phase has been reconstructed. ΔV is the result of a combination of factors, regarding the impact velocities of the colliding vehicles and the geometry of the impact (as eccentricity, etc.): for this reason, its value alone gives no clear indications on the actions which can be undertaken to reduce crash severity. This feature is particularly critical in some application fields, for example, in case of advanced driver assistance systems assessment in different accident scenarios. This work proposes the disaggregation of ΔV into two different 'a priori' parameters to assess crash severity of an impact before its occurrence: the crash momentum index, representing the impact configuration, and the closing velocity projected along the principal direction of force (Vr_pdof), as an index of the kinetic energy exchanged between the two vehicles. It is preliminarily shown how the proposed parameters can be calculated using established procedures - as momentum-based analysis - in a predictive ('a priori') approach. It is also evidenced how crash momentum index, Vr_pdof and the velocity change ΔV are in relation. To illustrate the procedure by means of examples, binary logistic regression on accident data is applied to correlate crash momentum index and ΔV to injury risk at Maximum Abbreviated Injury Scale level higher than 2. The use of crash momentum index as an additional severity index allows an improved correlation with injury risk, for the dataset used, in case of front and near side impacts. The use of the plane Vr_pdof- crash momentum index, on which curves at constant injury risk are drawn, provides clear indications on the possible strategies to reduce injury risk, as shown by generic examples to which the predictive procedure is applied.

Language: en