Development of point mass occupant injury criteria using event data recorders

Abstract

This paper presents an estimate of the probability of serious occupant injury in frontal crashes based on vehicle kinematics information. Occupant injury risk is developed by modeling the human as a point mass and computing the occupant impact velocity (OIV) using the flail space model. Event Data Recorder data provide vehicle kinematics information for real world crashes with known injury outcomes. A data set of 211 cases is used for methodology development and preliminary insight to the injury prediction capability of the metric. Using logistic regression, injury risk curves are generated for all data, a belted occupant subset and an unbelted occupant subset. Based on the models, an occupant restrained by an airbag and safety belt is found to have a lower risk of injury than an occupant only restrained by an airbag. A 50% probability of serious injury is found to correspond to an OIV of 11.2 m/s and 15.9 m/s for unbelted and belted occupants, respectively.