Sonstige
This study aimed at prediction of long bone fractures and assessment of lower extremity injury mechanisms in real world passenger car to pedestrian collision. For this purpose, two pedestrian accident cases with detail recorded lower limb injuries were reconstructed via combining MBS (Multi-body system) and FE (Finite element) methods. The code of PC Crash was used to determine the boundary conditions before collision, and then MBS models were used to reproduce the pedestrian kinematics and injuries during crash. Furthermore, a validated lower limb FE model was chosen to conduct reconstruction of injuries and prediction of long bone fracture via physical parameters of von Mises stress and bending moment. The injury outcomes from simulations were compared with hospital recorded injury data and the same long bone fracture patterns and positions can be observed. Moreover, the calculated long bone fracture tolerance corresponded to the outcome from cadaver tests. The result shows that FE model is capable to reproduce the dynamic injury process and is an effective tool to predict the risk of long bone fractures.
This study aimed at comparing head Wrap Around Distance (WAD) of Vulnerable Road User (VRU) obtained from the German in-depth Accident Database (GIDAS), the China in-depth Accident Database (CIDAS) and the Japanese in-depth Accident Database (ITARDA micro). Cumulative distribution of WAD of pedestrian and cyclist were obtained for each database (AIS2+) showing that WAD of cyclists were larger than the ones of pedestrians. Comparing three regions, the 50%tile WAD of GIDAS was larger than that of both Asian accident databases. Using linear regression that might predict WAD of pedestrians and cyclists from Impact speed and VRU height, WADs were calculated to be 206cm/219cm (Pedestrian/Cyclist) for GIDAS, 170cm/192cm for CIDAS and 211cm/235cm for ITARDA. In addition, this study may be helpful for reconsideration of WAD measurement alignment between accident reconstruction and test procedures.
Since a number of human models have been developed it appears sensible to use these models also in the accident analysis. Especially the understanding of injury mechanisms and probably even injury risk curves can be significantly improved when interesting accidents are reconstructed using human body models. However, an important limitation for utilising human models for accident reconstruction is the effort needed to develop detailed FE models of the accident partners or to prepare the human model reconstruction by running physical accident reconstructions. The proposed approach for using human models for accident reconstruction is to use simplified and parametric car models. These models can be adapted to the crash opponents in a fast and cost effective way. Although, accuracy is less compared to detailed FE models, the relevant change in velocity can be simulated well, indicating that the computation of a detailed crash pulse is not needed. Two frontal impact test accidents that were reconstructed experimentally and using the parametric car models are indicating sufficient correlation of the adapted parametric car models with the full scale crash reconstructions. However, further developments of the parametric models to be capable for the use in lateral impacts and rear impacts are needed. For the PC Crash simulation runs the output sampling rate is too large to allow sufficient analysis. In addition the performance appears to be too general.
Injury severity of e.g. pedestrians or bikers after crashes with cars that are reversing is almost unknown. However, crash victims of these injuries can frequently be seen in emergency departments and account for a large amount of patients every year. The objective of this study is to analyze injury severity of patients that were crashed into by reversing cars. The Hannover Medical School local accident research unit prospectively documented 43,000 road traffic accidents including 234 crashes involving reversing cars. Injury severity including the abbreviated injury scale (AIS) and the maximum abbreviated injury scale (MAIS) was analyzed as well as the location of the accident. As a result 234 accidents were included into this study. Pedestrians were injured in 141 crashes followed by 70 accidents involving bikers. The mean age of all crash victims was 57 -± 23 years. Most injuries took place on straight stretches (n = 81) as well as parking areas (n = 59), entries (n = 36) or crossroads (n = 24). The AIS of the lower extremities was highest followed by the upper extremities. The AIS of the neck was lowest. The mean MAIS was 1.3 -± 0.6. The paper concludes that the lower extremities show the highest risk to become injured during accidents with reversing cars. However, the risk of severe injuries is likely low.