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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.
The paper aims to study the injury risk and kinematics of pedestrians involved in different passenger vehicle collisions. Furthermore, the difference of pedestrian kinematics in the accidents involved minivan and sedan was analyzed. The 18 sample cases of passenger car to pedestrian collisions were selected from the database of In-depth Investigation of Vehicle Accident in Changsha of China (IVAC),of which the 12 pedestrian accidents involved in a minivan impact for each case, and the 6 accidents in a sedan impact for each. The selected cases were reconstructed by using mathematical models of pedestrians and accident vehicles in a multi-body dynamic code MADYMO environment. The logistic regression models of the risks for pedestrian AIS 3+ injuries and fatalities were developed in terms of vehicle impact speed by analyzing the minivan-pedestrian and sedan-pedestrian accidents. The difference of pedestrian kinematics was identified by comparing the results from reconstructed pedestrian accidents between the minivans and sedans collisions. The result shows that there is a significant correlation among the impact speed and the severity of pedestrian injuries. The minivan poses greater risk to pedestrian than sedan at the same impact speed. The kinematics of pedestrian was greatly influenced by vehicle front shape.
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.
There is a need for detecting characteristics of pedestrian movement before car-pedestrian collisions to trigger a fully reversible pedestrian protection system. For this purpose, a pedestrian sensor system has been developed. In order to evaluate the effectiveness of the sensor system, the in-depth knowledge of car-pedestrian impact scenarios is needed. This study aims at the evaluation of the sensor system. The accident data are selected from the STRADA database. The accident scenarios available in this database were evaluated and the knowledge of the most common scenarios was developed in terms of the pedestrian trajectory, the pedestrian speed, the car trajectory, the car velocity, etc. A mathematical model was then established to evaluate the sensor system with different detective angles. It was found that in order to detect all the pedestrians in the most common scenarios on time the sensor detective angle must be kept larger than 60 degrees.
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.
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).
The paper presents a methodology for the benefit estimation of several secondary safety systems for pedestrians, using the exceptional data depth of GIDAS. A total of 667 frontal pedestrian accidents up to 40kph and more than 500 AIS2+ injuries have been considered. In addition to the severity, affected body region, exact impact point on the vehicle, and the causing part of every injury, the related Euro NCAP test zone was determined. One results of the study is a detailed impact distribution for AIS2+ injuries across the vehicle front. It can be stated, how often a test zone or vehicle part is hit by pedestrians in frontal accidents and which role the ground impact plays. Basing on that, different secondary safety measures can be evaluated by an injury shift method concerning their real world effectiveness. As an example, measures concerning the Euro NCAP pedestrian rating tests have been evaluated. It was analysed which Euro NCAP test zones are the most effective ones. In addition, real test results have been evaluated. Using the presented methodology, other secondary safety like the active bonnet (pop-up bonnet) or a pedestrian airbag measures can be evaluated.
One goal of the assessment of the crashworthiness of passenger cars is to characterize the potential of injury outcome to occupants of cars involved in an accident. This can be achieved by the help of an index that puts the number of injured occupants of passenger cars in relation to the number of cars involved in an accident. As a consequence, this index decreases with a lower potential of injury and rises with a higher number of injuries while assuming a fixed number of accidents. Another index is introduced that uses an economical weighting of each injury level. The consequential injury costs are calculated using the average economical costs for lightly, severely and fatally injured persons. The calculation of the safety indices is based on an anonymized sample of accident data provided by the Federal Statistical Office. An index of Mercedes passenger car drivers depending on the year of registration between 1991 and 2006 is compared to the index of drivers of cars of other makes within the same range of registration years.
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.
The fact that ADAC Air Rescue handles approximately 4,000 road accident missions every year gave rise to set up an accident research programme for which ADAC Air Rescue provides its data. This data is of initial informational quality and will be supplemented by data from the police, experts, fire brigades as well as hospitals and forensic institutes. Although the number of cases is still rather low, certain tendencies can be identified. The causes for most accidents occur when joining or intersecting traffic, followed by speeding in road bends and tailgating. Many accidents involve HGV rear end collisions, often causing serious injuries, considerable damage and technical problems for the rescue operations. With regard to the various impact types, it has become obvious that most of the extremely serious injuries are inflicted during a passenger car side impact. In addition, access to and removal of trapped passengers is becoming more and more complicated, partly due to the increasing use of high-strength materials, and rescue operations tend to be more time consuming.