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In this study, the mean profile depth (MPD) that expresses roughness of road pavements was calculated using the road survey equipment vehicle and the calculated MPD was compared with the real number of traffic accidents. The analysis method used in this study was to classify the appropriate clustering in relation to traffic accidents using the K-means clustering and to compare this with the presence of traffic accidents via the MPDs to derive the result. K-means clustering was used in the analysis method and four clusters were found using the clustering analysis results. The center of each cluster was 0.627, 0.850, 1.118, and 1.237, respectively. The result of this study is expected to be utilized as foundational research in the traffic safety area.
Whiplash injuries are characterized by the high variability of its symptoms and by the subjectivity of its diagnosis, which sometimes leads to frauds perpetrated by victims of rear-end impacts. It is estimated that whiplash injuries cost annually about 10.000 million Euros in Europe. Therefore, the aim of this study was to investigate the influence of the dynamics of the accident in which the victim was involved in the probability of development of whiplash associated injuries. In the presented methodology, first an accident reconstruction is performed where the dynamics of the accident is determined. This is carried out using the software PC-Crash, police and insurance companies' data. Then biomechanical injuries criteria related with whiplash injuries are evaluated. For the evaluation of the probability of having whiplash injuries, the Neck Injury Criterion (NIC) of the victim and the mean acceleration of the vehicle were evaluated. Then, with medical reports, the results of the accident reconstruction are correlated with the reported injuries. Some examples are presented. The results obtained indicate that the study of the dynamics of the road accidents in which the victims were involved could be used as an auxiliary of the prognosis of whiplash injuries and is important for a precise diagnosis of this type of injuries.
In Germany the number of casualties in passenger car to pedestrian crashes has been reduced by a considerable amount of 40% as regards fatalities and 25% with regard to seriously injured pedestrians since the year 2001. Similar trends can be seen in other European countries. The reasons for that positive development are still under investigation. As infrastructural or behavioral changes do in general take a longer time to be effective in real world, explanations related to improved active and passive safety of passenger vehicles can be more relevant in providing answers for this trend. The effect of passive pedestrian protection " specified by the Euro NCAP pedestrian test result " is of particular interest and has already been analyzed by several authors. However, the number of vehicles with some valid Euro NCAP pedestrian score (post 2002 rating) was quite limited in most of those studies. To overcome this problem of small datasets German National Accident Records have been taken to investigate a similar objective but now based on a much bigger dataset. The paper uses German National Accident Records from the years 2009 to 2011. In total 65.140 records of pedestrian to passenger car crashes have been available. Considering crash parameters like accident location (rural / urban areas) etc., 27.143 of those crashes have been classified to be relevant for the analysis of passive pedestrian safety. In those 27.143 records 7.576 Euro NCAP rated vehicles (post 2002 rating) have been identified. In addition it was possible to identify vehicles which comply with pedestrian protection legislation (2003/102/EG) where phase 1 came into force in October 2005. A significant correlation between Euro NCAP pedestrian score and injury outcome in real-life car to pedestrian crashes was found. Comparing a vehicle scoring 5 points and a vehicle scoring 22 points, pedestrians" conditional probability of getting fatally injured is reduced by 35% (from 0.58% to 0.37%) for the later one. At the same time the probability of serious injuries can be reduced by 16% (from 27.4% to 22.9%). No significant injury reducing effect, associated with the introduction of pedestrian protection legislation (phase 1) was detected. Considerable effects have also been identified comparing diesel and gasoline cars. Higher engine displacements are associated with a lower injury risk for pedestrians. The most relevant parameter has been "time of accident", whereas pedestrians face a more than 2 times higher probability to be fatally injured during night and darkness as compared to daytime conditions.
Impact severity is a fundamental measure for all in-depth crash investigation projects. One methodology used in the UK is based on the US Calspan software package CRASH3. The UK- in-depth crash investigation studies routinely use AiDamage3 a software package which is based on an updated version of the original CRASH3 algorithm, including enhancements to the vehicle stiffness coefficients. Real world accident-damaged vehicles are measured and their crush is correlated with a library of stiffness coefficients. These measurements are then used, along with other parameters, to calculate the crash energy and equivalent changes of velocity of the vehicles (delta-v), which is a measure of the impact severity. UK in-depth accident studies routinely validate the crash severity methodologies applied as the vehicle fleet changes. This is achieved by analysing crash test data and using the appropriate residual crush damage and other inputs to AiDamage3 and checking the program- outputs with the known crash severity parameters. This procedure checks, at least in part, the default stiffness values in the data libraries and the reconstruction methods used.
This study is aimed to investigate the correlations of impact conditions and dynamic responses with the injuries and injury severity of child pedestrians by accident reconstruction. For this purpose, the pedestrian accident cases were selected from Sweden and Germany with detailed information about injuries, accident cars, and accident environment. The selected accident cases were reconstructed using mathematical models of pedestrian and passenger car. The pedestrian models were generated based on the height, weight, and age of the pedestrian involved in accidents. The car models were built up based on the corresponding accident car. The impact speeds in simulations were defined based on the reported data. The calculated physical quantities were analyzed to find the correlation with injury outcomes registered in the accident database. The reconstruction approaches are discussed in terms of data collection, estimating vehicle impact speeds, pedestrian moving speeds and initial posture, secondary ground impact, validity of the mathematical models, as well as impact biomechanics.