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A total survey of road traffic accidents involving most severely injured, defined as sustaining a polytrauma or severe monotrauma (ISS > 15) or being killed, was conducted over 14 months in a large study region in Germany. Data on injuries, pre-clinical and clinical care, crash circumstances and vehicle damage were obtained both prospectively and retrospectively from trauma centers, dispatch centers, police and fire departments. 149 patients with a polytrauma and eight with a severe monotrauma were recorded altogether. 22 patients died in hospital. Another 76 victims had deceased at the accident scene. In 2008, 49 % of patients treated with life-threatening injuries were car or van occupants, 21 % motorcyclists, 18 % cyclists and 10 % pedestrians. Among fatalities at the scene, vehicle occupants constituted an even larger portion. The number of road users with life-threatening trauma in the region was extrapolated to the German situation. It suggests that 10 % among the "seriously injured" as defined in national accident statistics are surviving accident victims with a polytrauma or severe monotrauma.
Pelvic fracture, cracking or breaking of a portion of the pelvis are extremely common injuries in the side impact collisions of motor vehicles. Due to both its shape and structural architecture, mechanics of the pelvic bone is complicated. There is a lack of knowledge regarding the dynamic behavior of the pelvis and its biomechanical tolerance under impact environment. Hence this study is aimed at the understanding of the mechanical response of the human pelvis with three-dimensional finite element (FE) models, under side impact load, applied through a structure, equivalent to a car door. The door structure was modeled, considering few layers, consisting of foam (Styrodur®, 3035 CS), plastic (UHMWPE), steel, glass and steel, putting them in series. A soft tissue layer (equivalent to fat) was also considered on the greater trochanter location. These FE models (with and without the car door structure) were analyzed with ANSYS-LS-DYNA-® dynamic finite element software to compare the effect of the car door padding system for shock absorption. It was observed that with proper combination of shock absorbing material (foam, etc.) and its thickness, the transmission of impact load to the body part (pelvis, etc.) from the outer surface of the car door could be reduced.
This paper reviews briefly the evolution of the investigation of transport accidents from the early beginnings when individual events were studied but systematic data was not collected. In the transport modes other than on the roads, accident investigation early on, even of single events, was important in introducing safety improvements. Road accidents, however, evolved enormously with the growth of car ownership without any comparable political response to the consequent deaths and injuries, equivalent to what happened with the other modes. From the 1950s data bases started to contribute to our knowledge of the epidemiology of road traffic injuries, and in-depth sample studies have contributed much to the body of knowledge in the last 30 years. However, even the basic input and output variables of a crash, its severity and the seriousness of the outcomes in terms of injuries and their consequences are not complete or agreed upon. Issues of experimental design and sampling are discussed. It is proposed that the most important area for current research to address is the effect of population variations on injury outcomes. The need for the establishment of good data bases for active safety issues is emphasised with the consequent need for better links between the research community and the police.
A means of assessing the passive safety of automobiles is a desirable instrument for legislative bodies, the automobile industry, and the consumer. As opposed to the dominating motor vehicle assessment criteria, such as engine power, spaciousness, aerodynamics and consumption, there are no clear and generally accepted criteria for assessing the passive safety of cars. The proposed method of assessment combines the results of experimental safety tests, carried out according to existing legally prescribed or currently discussed testing conditions, and a biomechanical validation of the loading values determined in the test. This evaluation is carried out with the aid of risk functions which are specified for individual parts of the body by correlating the results of accident analysis with those obtained by computer simulation. The degree of conformance to the respective protection criterion thus deduced is then weighted with factors which take into account the frequency of occurrence and the severity of the accident on the basis of resulting costs. Each of the test series includes at least two frontal and one lateral crash test against a deformable barrier. The computer-aided analysis and evaluation of the simulation results enables a vehicle-specific overall safety index as well as partial and individual safety values to be determined and plotted graphically. The passive safety provided by the respective vehicle under test can be defined for specific seating positions, special types of accident, or for individual endangered parts of the body.
This study aimed at developing an injury estimation algorithm for AACN technologies for Germany and compared them to findings based on Japanese data. The data to build and to verify the algorithm was obtained from the German in-depth Accident Database (GIDAS) and split into a training and a validation dataset. Significant input variables and the generalized linear regression model to predict severe injuries (ISS>15) were selected to maximize area under the receiver operating characteristic curve (AUC). Probit regression with the input parameter multiple impact, delta v, seatbelt use and impact direction gave the largest AUC of 0.91. Sensitivity of the algorithm was validated at 90% and specificity at 76% for an injury risk threshold of 2%. It appears that no major differences between Japan and Germany exist for injury estimation based on delta v and impact direction. However, far side impact and multiple crash events appear to be associated with a larger risk increase in the German data.
The main objective of EC CASPER research project is to reduce fatalities and injuries of children travelling in cars. Accidents involving children were investigated, modelling of human being and tools for dummies were advanced, a survey for the diagnosis of child safety was carried out and demands and applications were analysed. From the many research tasks of the CASPER project, the intention of this paper is to address the following: • In-depth investigation of accidents and accident reconstruction. These will provide important points for the injury risk curve, in order to improve it. Different accident investigation teams collected data from real road accidents, involving child car passengers, in five different European countries. Then, a selection of the most appropriate cases for the injury risk curve and the purposes of the project was made for an in-depth analysis. The final stage of this analysis was to conduct an accident reconstruction to validate the results obtained. The in-depth analysis included on-scene accident investigation, creating virtual simulations of the accident/possible reconstruction, and conducting the reconstruction. In the cases of successful reconstructions, new points were introduced to the injury risk curves. Accident reconstructions of selected cases were carried out in test laboratories as the next step following in-depth road accident investigation. These cases were reconstructed using similar child restraint systems (CRS) and the same type make and model as in the real accidents. Reconstructing real cases has several limitations, such as crash angle, cars" approximation paths and crash speed. However, a few changes and applications on the testing conditions were applied to reduce the limitations and improved the representations of the real accidents. After conducting the reconstructions, a comparison between the deformations of the cars on the real accident and the vehicles from the reconstructions was made. Additionally, a correlation between the data captured from the dummies and the injury data from the real accident was sought. This finalises an in-depth analysis of the accident, which will provide new relevant points to the injury risk curve. The CASPER project conducted a large research programme on child safety. On technical points, a promising research area is the developing injury risk curves as a result of in-depth accident investigations and reconstructions. This abstract was written whilst the project was not yet finished and final results are not yet known, but they will be available by the time of the conference. All the works and findings will not necessarily be integrated in the industrial versions of evaluation tools as the CASPER project is a research program.
Causation patterns and data collection blind spots for fatal intersection accidents in Norway
(2010)
Norwegian fatal intersection accidents from the years 2005-2007 were analysed to identify any causation patterns among their underlying contributing factors, and also to evaluate whether the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to perform causation pattern analysis. A total of 28 fatal accidents were analysed. Details on crash contributing factors for each driver in each crash were first coded using the Driving Reliability and Error Analysis Method (DREAM), and then aggregated based on whether the driver was going straight or turning. Analysis results indicate that turning drivers to a large extent are faced with perception difficulties and unexpected behaviour from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers going straight on the other hand have less perception difficulties. Instead, their main problem is that they largely expect turning drivers to yield. When this assumption is violated, they are either slow to react or do not react at all. Contributing factors often pointed to in literature, e.g. high speed, drugs and/or alcohol and inadequate driver training, played a role in 12 of 28 accidents. While this confirms their prevalence, it also indicates that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, information on blunt end factors (those more distant in time/space, yet important for the development of events) was more limited than information on sharp end factors (those close in time/space to the crash). A possible explanation is that analysts may view some blunt end factors as event circumstances rather than contributing factors in themselves, and therefore do not report them. There was also an asymmetry in terms of reported obstructions to view due to signposts and vegetation. While frequently reported as contributing for turning drivers, they were rarely reported as contributing for their counterparts in the same accidents. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver legally held liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator mindset needs addressing to avoid future bias in crash investigation reports.
Accident data shows that the vast majority of pedestrian accidents involve a passenger car. A refined method for estimating the potential effectiveness of a technology designed to support the car driver in mitigating or avoiding pedestrian accidents is presented. The basis of the benefit prediction method consists of accident scenario information for pedestrian-passenger car accidents from GIDAS, including vehicle and pedestrian velocities. These real world pedestrian accidents were first reconstructed and the system effectiveness was determined by comparing injury outcome with and without the functionality enabled for each accident. The predictions from Volvo Cars" general Benefit Estimation Model are refined by including the actual system algorithm and sensing models for a relevant car in the simulation environment. The feasibility of the method is proven by a case study on a authentic technology; the Auto Brake functionality in Collision Warning with Full Auto Brake and Pedestrian Detection (CWAB-PD). Assuming the system is adopted by all vehicles, the Case Study indicates a 24% reduction in pedestrian fatalities for crashes where the pedestrians were struck by the front of a passenger car.
Injury probability functions for pedestrians and bicyclists based on real-world accident data
(2017)
The paper is focusing on the modelling of injury severity probabilities, often called as Injury Risk Functions (IRF). These are mathematical functions describing the probability for a defined population and for possible explanatory factors (variables) to sustain a certain injury severity. Injury risk functions are becoming more and more important as basis for the assessment of automotive safety systems. They contribute to the understanding of injury mechanisms, (prospective) evaluation of safety systems and definition of protection criteria or are used within regulation and/or consumer ratings. In all cases, knowledge about the correlation between mechanical behavior and injury severity is needed. IRFs are often based on biomechanical data. This paper is focusing on the derivation of injury probability models from real world accident data of the GIDAS database (German In-depth Accident Study). In contrast to most academic terms there is no explicit term definition or definition of creation processes existing for injury probability models based on empirical data. Different approaches are existing for such kind of models in the field of accident research. There is a need for harmonization in terms of the used methods and data as well as the handling with the existing challenges. These are preparation of the dataset, model assumptions, censored/unknown data, evaluation of model accuracy, definition of dependent and independent variable, and others. In the presented study, several empirical, statistical and phenomenological approaches were analyzed regarding their advantages and disadvantages and also their applicability. Furthermore, the identification of appropriate prediction parameters for the injury severity of pedestrians has been considered. Due to its main effect on injuries of pedestrians and bicyclists, the importance of the secondary impact has also been analyzed. Finally, the model accuracy, evaluated by several criteria, is the rating factor that gives the quality and reliability for application of the resulting models. After the investigation and evaluation of statistical approaches one method was chosen and appropriate prediction variables were examined. Finally, all findings were summarized and injury risk functions for pedestrians in real world accidents were created. Additionally, the paper gives instructions for the interpretation and usage of such functions. The presented results include IRFs for several injury severity levels and age groups. The presented models are based on a high amount of real world accidents and describe very well the injury severity probability of pedestrians and bicyclists in frontal collisions with current vehicles. The functions can serve as basis for the evaluation of effectiveness of systems like Pedestrian-AEB or Bicycle-AEB.
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.