Prediction of Occupant Injuries for Improved eCall Efficiency

Abstract

Especially in emerging markets, no emergency infrastructure is established. In case of an accident, passing road users need to call for help or the ambulance. An automated eCall to friends, family or in future directly to the rescue control with transmission of GPS position, probable injury pattern and injury severity could significantly improve the rescue chain and would save lives in large scale. Initial approaches to the prediction of an injury pattern were investigated in this paper. A simulation model of a reference vehicle and with a hybrid III 50 percentile dummy was built by using the program MADYMO. A large amount of real accident data was processed using an algorithm created in MATLAB. This made it possible to adapt the acceleration data with identical rules and to determine the different restraint system ignition times. The algorithm allows the data to be used in the simulation model. Furthermore, the corresponding accident descriptions were analysed and translated into protection criteria level by means of literature. For the subsequent evaluation, the assessment protocol (Version 8.0.3) of the European New Car Assessment Programme (EuroNCAP) was used. To validate the model, an ordinal rating system was created to compare the ratings of the simulation and the injury descriptions. The results indicate a good prediction of the injury patterns with an agreement of 39.56 percent. Especially considering that a large number of influencing parameters are unknown.