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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.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
Analysis of pedestrian leg contacts and distribution of contact points across the vehicle front
(2015)
Determining the risk to pedestrians that are impacted by areas of the front bumper not currently regulated in type-approval testing requires an understanding of the target population and the injury risk posed by the edges of the bumper. National statistics show that approximately 10% of all accident casualties are pedestrians, with 20% to 30% of these pedestrian casualties being killed or seriously injured. However, the contact position across the front of the bumper is not recorded in national statistics and so in-depth accident databases (OTS, UK and GIDAS, Germany) were used to examine injury risk in greater detail. The results showed that some injury types and severities of injuries appear to peak around the bumper edges. Although there are sometimes inconsistencies in the data, generally there is no evidence to suggest that the edges of the bumper are less likely to be contacted or cause injury.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.
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.