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Von 2006 bis 2015 hat die Zahl der bei Unfällen mit Personenschäden Beteiligten unter Alkoholeinfluss um 36 % abgenommen. Im gleichen Umfang (36%) hat sich auch die Anzahl der Alkoholunfälle mit Personenschaden reduziert. Nach wie vor tritt bei Pkw-Fahrern Alkohol als Unfallursache am häufigsten in der Altersgruppe der 21- bis 24-jährigen Männer auf, gefolgt von den Gruppen der männlichen 25- bis 34-jährigen Fahrer und der 18- bis 20-Jährigen. Die Anzahl der an Unfällen mit Personenschaden beteiligten alkoholisierten männlichen Pkw-Fahrer fällt etwa 6-mal so hoch aus wie die der weiblichen. Alkoholunfälle mit Personenschaden ereignen sich am häufigsten in den Abend- und frühen Morgenstunden und insbesondere in den Wochenendnächten. Unter den Verursachern dieser nächtlichen Freizeitunfälle sind junge Erwachsene überproportional häufig vertreten. Seit 2001 gilt in Deutschland eine 0,5-Promille-Grenze für Kraftfahrer. Im Jahr 2005 wurde eine Null-Promille-Grenze für Gefahrguttransporte eingeführt. Im August 2007 ist das Alkoholverbot für Fahranfänger in Kraft getreten. Dieses gilt für alle jungen Fahrer unter 21 Jahren sowie für Fahranfänger, die sich noch in der zweijährigen Probezeit befinden, unabhängig von ihrem Alter. Die Gefährdung der Verkehrssicherheit durch drogenbeeinflusste Kraftfahrer hat seit den 90er Jahren an Bedeutung gewonnen. Daher wurden verschiedene gesetzliche Neuregelungen eingeführt. Hierzu zählt insbesondere die Einführung eines Ordnungswidrigkeitentatbestands für das Fahren unter dem Einfluss bestimmter psychoaktiver Substanzen im Jahr 1998. Weiterhin wurden Ausbildungsmaßnahmen für die Polizei zur besseren Erkennung einer Drogenwirkung bei Kraftfahrern erarbeitet und in die Praxis umgesetzt. Vor diesem Hintergrund ist die Dokumentation der Unfallursache "andere berauschende Mittel" deutlich angestiegen, liegt aber immer noch um ein Vielfaches niedriger als die der Unfallursache Alkohol.
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.
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.