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- Pedestrian (4) (entfernen)
Recently, EuroNCAP updated the upper legform test protocols. The main objective of this study is to establish the upper legform test in KIDAS (Korean In-depth Accident Study) taking into account domestic pedestrian accident data as well as anthropometric data to protect elderly pedestrians whose average height and weight is much smaller and lighter than other age groups, especially compared to Europeans. Therefore 230 cases of pedestrian accidents from KIDAS were investigated to explore the injury severity of body regions as well as age related injury patterns. Injuries of all body regions were examined, with a special focus on injuries of abdomen and pelvic area. On the other hand, in order to explore Korea's pedestrian accident environment, national police data and KIDAS (Korean In-depth Accident Study) data were compared. The results should be taken into account in future analyses and possible improvements, such as regulations and KNCAP test protocols, of the pedestrian safety policy in Korea.
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).
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 proportion of older road users is increasing because of demographic change (in the group 65+ from current 18% to about 24% by 2030). The mobility needs of people 65+ often differ from those of younger people. Seniors (65+) are already more involved in fatal accidents than younger road users. According to the age development, the senior share of road deaths in the EU of today is increasing nearly one-fifth to one-third. From the in-depth analysis of accidents generic simulation models were developed. Attention has been paid both to psycho-physical characteristics as well as on the social and physical environment and their specifics in conjunction with seniors. By simulating the defined scenarios and varying the defined relevant parameters, accident influencing factors were examined as a basis for avoidance. In addition, the parameters were varied to show the influence from the vehicle, the pedestrian and the infrastructure to avoid the accident or to characterize the conditions for which the accident is inevitable.