Sonstige
The number of injured car occupants decreases constantly. Nevertheless, they account for nearly 50% of all fatalities and about 44% of all seriously injured persons in German traffic accidents. Further reductions of casualties require multiple efforts in all parts of traffic safety. In this paper a detailed analysis of the important pre-hospital rescue phase was done. The basis for future improvements is the knowledge about injury causation of car occupants in combination with other corresponding influence factors. For that reason more than 1.200 severe (AIS3+) injuries of frontal car occupants were analyzed. For the most relevant injuries of car occupants multivariate analysis models were created to predict the probability of these injuries in a real crash scenario. In addition to the collision severity different influence factors like impact direction, seat belt usage, age of the occupant, and gender were analyzed. Furthermore, the models were checked regarding the goodness of fit and all results all results were checked concerning their robustness. The prediction models were created on the basis of 5.000 car accidents. Afterwards, the models were validated using 4.000 different car accidents. The prediction of the probability of severe injuries could be used for different applications in the field of traffic safety. One possibility is the implementation of the models in a tool for the on-the-spot diagnosis. The background for the development of such applications is the fact, that there are only limited diagnostic possibilities available at the accident scene. Nevertheless, the rescue forces have to make essential decisions like the alerting of the necessary medical experts, appropriate treatment, the type of transportation and the choice of an adequate hospital. These decisions quite often decide between life and death or influence the long-term effects of injured persons. At this point, indications of expectable injuries could help enormously. To enable even persons with limited technical knowledge to use the tool, a procedure was developed that facilitates the assumption of the given crash severity. Another important possibility for the application of the prediction models is the use for the qualification of information sent by e-call systems.
The share of high-tensile steel in car bodies has increased over the last years. While occupant safety has generally benefited from this measure, there is a potential risk that, as a result, rescue time may increase considerably. In more than 60% of all car occupant fatalities a technical rescue has been necessary. These are in particular those cases where occupants die immediately at the accident scene. Therefore, in these cases "rescue time" is a very sensitive parameter. In addition to the general analysis of the need of technical rescue and the actual rescue time depending on model years, the injury pattern of occupants requiring technical rescue will be analysed to provide advice for rescue teams. Furthermore, a detailed analysis of rescue measures for the most popular car models depending on the safety cell design is given.
Every second counts when human lives are at stake. The increasingly safe design of vehicles presents rescuers with a serious challenge. Faced with high-strength steels and body reinforcements, even the most powerful cutters reach their limits. Therefore, incident commanders require information on the technical features and components installed, directly in the vehicle. Several tests have shown that such information helps to save valuable minutes. Therefore, a standardised A4 "rescue sheet" containing information on the location of cabin reinforcements, the tank, the battery, airbags, gas generators, control units etc. " and indicating adequate cutting points must be used throughout Europe. Hopefully, in a few years, the new eCall emergency call system will be in place everywhere in Europe. The system will transmit the relevant vehicle-specific data directly to the rescuers on-site. Until then, we need a simple and effective solution that saves lives.