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The aim of this study was to evaluate the performance and accuracy of Event Data Recorders (EDRs). The analysis was based on J-NCAP crash tests from 2006"2007, with the corresponding EDR datasets. The pre-crash velocity, maximum delta-V and delta-V versus time history data recorded in the EDRs were compared with the reliable crash test data. The difference between the EDR pre-crash velocity and the laboratory test speed was less than 4 percent. In contrast, in several cases the maximum delta-V and delta-V versus time history data obtained from the EDRs showed uncertainty of measurement in comparisons with the reliable delta-V data. The difference in maximum delta-V in these comparisons was more than 5 percent in 10 of 14 tests and more than 10 percent in 4 of 14 tests. The EDRs underestimated the maximum delta-V in almost all tests. It was also concluded that the calculated acceleration from the EDR delta-V versus time history data showed good agreement with the instrumented accelerometer signal during the collision in almost all tests.
The incidence and treatment of sternal fractures among traffic accidents are of increasing importance to ensure best possible outcomes. Analysis of technical indicators of the collision, preclinical and clinical data of patients with sterna fractures from 1985-2004 among 42,055 injured patients were assessed by an Accident Research Unit. Two time groups were categorized: 1985-1994 (A) vs. 1995-2004 (B). 267/42,055 patients (0.64%) suffered a sterna fracture. Regarding the vehicle type, the majority occurred after car accidents in 0.81% (251/31,183 pts), followed by 0.19% (5/2,633pts) driving motorbike, and 0.11% (4/3,258pts) driving a truck. 91% wore a safety belt. Only 13% of all passengers suffering a sternal fracture had an airbag on board (33/255 car/trucks), with an airbag malfunction in 18%. The steering column was deformed in 39%, the steering wheel in 36%. Cars in the recent years were significantly older (7.67-±5 years (B) vs. 5.88-±5 years (A), p=0.003). Cervical spine injuries are frequent (23% vs. 22%), followed by multiple rib fractures (14% vs. 12%) and lung injuries (12% vs. 11%). We found 9/146 (6%) and 3/121 patients (3%) with heart contusion among the 267 sternal fractures. MAIS was 2.56-±1.3 vs. 2.62-±1.3 (A vs. B, p=0.349). 18% of patients were polytraumatized, with 11.2% dying at the scene, 2.3% in the hospital. Sternal fractures occur most often in old cars to seat-belted drivers often without any airbag. Severe multiple rib fractures and lung contusion are concomitant injuries in more than 10% each indicating the severity of the crash. Over a twentyyear period, the injury severity encountered was not different with 18% polytrauma patients suffering sternal fractures.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
In Germany, in-depth accident investigations are carried out in the Hannover area since 1973. In 1999 a second region was added with surveys in Dresden and the surrounding area. Internationally, the acronym GIDAS (German In-Depth Accident Study) is commonly used for these surveys. Compared to many other countries, the sample sizes of the GIDAS surveys are much larger. The goal is to collect 1.000 accidents involving personal injuries per year and region. Data collection takes place by using a sampling procedure, which can be interpreted as a two-stage process with time intervals as primary units and accidents as secondary units. An important question is, to what extend these samples are representative for the target population from which they are drawn. Analyses show, for example, that accidents with persons killed or seriously injured are overrepresented in the samples compared to accidents with slightly injured persons. This means, that these data are subject to biases due to uncontrolled variation of sample inclusion probability. Therefore, appropriate weighting and expansion methods have to be applied in order to adjust or correct for these biases. The contribution describes the statistical and methodological principles underlying the GIDAS surveys with respect to sampling procedure, data collection and expansion. In addition, some suggestions regarding potential improvements of study design are made from a methodological point of view.
The bicyclist accidents were analyzed to get better understanding of the occurrences and frequency of the accidents, injury distributions, as well as correlation of injury severity/outcomes with engineering and human factors in two different countries of China and Germany. The accident cases that occurred from 2001 to 2006 were collected from IVAC database in Changsha and GIDAS database in Hannover. Based on specified sampling criteria, 1,570 bicyclist cases were selected from IVAC database in Changsha, and 1806 cases were collected from Hannover, documented in GIDAS database. Statistical analyses were carried out by using these selected data. The results from the statistical analysis are presented and discussed in this study.
The sequence of accident events can be classified by three essential phases, the pre-crash-sequence, the crash-sequence and the post-crash-sequence. The level of reliability of the information in the GIDAS-database (German In Depth Accident Study) is provided predominantly on the passive side. The period to evaluate active safety systems begins already in the pre-crash-sequence. The assessment of the potential of sensor- or communication-based active safety systems can only be accomplished by a detailed analysis of the pre-crash-phase. Hence the necessity to analyze the early period of the accident event in detail arises. This is possible with the help of the digital sketches of the accident site and the simulation of the accident by a simulation method of the VUFO GmbH. After simulating the pre-crash scenario it is possible to generate additional and standardized data to describe the pre-crash-sequences of an accident in a very high detail. These data are documented in a second database called the GIDAS Pre-Crash-Matrix (PCM). The PCM contains various tables with all relevant data to reproduce the pre-crash-sequence of traffic accidents from the GIDAS database until 5 seconds before the first collision. This includes parameters to describe the environment data, participant data and motion or dynamic data. This paper explains the creation of the PCM, the simulation itself and the contents and structure of the PCM. With this information of the pre-crash-sequence for various accident scenarios an improved benefit estimation and development of active safety systems can be made possible.
The data situation for quantifying the proportion of accidents avoided by the introduction of active safety systems is incomplete, since there is generally no data available on the accidents avoided by the technology in question. In this paper, a split-register approach is suggested and compared with the classical case-control approach known from epidemiologic applications. Provided a set of assumptions hold, which can reasonably be made in such data situations, the split register approach allows inferences on the population accident risk. For both approaches the benefits of basing the analysis on the results of a logistic regression to adjust for confounding factors are outlined. The biasing effects of violating key assumptions are discussed and the split-register approach is demonstrated using the example of the active safety system ESP with data from the German in-depth accident study GIDAS.
To elucidate the risk of pedestrians, bicycle and motorbike users, data of two accident research units from 1999 to 2014 were analysed in regard to demographic data, collision details, preclinical and clinical data using SPSS. 14.295 injured vulnerable road users were included. 92 out of 3610 pedestrians ("P", 2.5%), 90 out of 8307 bicyclists ("B", 1.1%) and 115 out of 4094 motorcycle users ("M", 2.8%) were diagnosed with spinal fractures. Thoracic fractures were most frequent ahead of lumbar and cervical fractures. Car collisions were most frequent mechanism (68, 62 and 36%). MAIS was 3.8, 2.8 and 3.2 for P, B and A with ISS 32, 16 and 23. AIS-head was 2.2, 1.3 and 1.5). Vulnerable road users are at significant risk for spine fractures. These are often associated with severe additional injuries, e.g. the head and a very high overall trauma severity (polytrauma).
Introduction: Spine injuries pose a considerable risk to life and quality of life. The total number of road deaths in developed countries has markedly decreased, e.g. in Germany from over 20000 in 1970 to less than 4000 in 2010, but little is known how this is reflected in the burden of spine fractures of motor vehicle users. In this study, we aimed to show the actual incidence of spine injuries among drivers and front passengers and elucidate possible dependencies between crash mechanisms and types of injuries.
This study aims to analyze spine injuries in motor vehicle accidents. Between 1985 and 2004 the Hannover accident research unit documented 18353 accidents. We identified 161 front passengers (0.53%) with cervical spine injuries, 84 (0.28%) with thoracic and 95 (0.31%) with lumbar injuries. Technical and medical data was reviewed. Patients" records were retrieved. X-rays were evaluated and fractures were classified according to the Magerl classification. 68% and 57% of thoracic and lumbar fractures occurred in accidents with multiple impacts. Delta-v was 50, 40 and 40 kph in passengers with cervical, thoracic and lumbar spine, resp. Passengers with spinal fractures frequently showed numerous concomitant injuries, e.g. additional vertebral fractures. The influence of seat belts and airbags is discussed. Patient work-up has to include a thorough investigation for additional injuries.