As the official German catalogue of accident causes has difficulty in matching the increasing demands for detailed psychologically relevant accident causation information, a new system, based on a "7 Steps" model, so called ACASS, for analyzing and collecting causation factors of traffic accidents, was implemented in GIDAS in the year 2008. A hierarchical system was developed, which describes the human causation factors in a chronological sequence (from the perception to concrete action errors), considering the logical sequence of basic human functions when reacting to a request for reaction. With the help of this system the human errors of accident participants can be adequately described, as the causes of each range of basic human functions may be divided into their characteristics (influence criteria) and further into specific indicators of these characteristics (e.g. distraction from inside the vehicle as a characteristic of an observation-error and the operation of devices as an indication for distraction from inside the vehicle. The causation factors accordingly classified can be recorded in an economic way as a number is assigned to each basic function, to each characteristic of that basic function and to each indicator of that characteristic. Thus each causation factor can be explicitly described by means of a code of numbers. In a similar way the causation factors based on the technology of the vehicle and the driving environment, which are also subdivided in an equally hierarchical system, can be tagged with a code. Since the causes of traffic accidents can consist of a variety of factors from different ranges and categories, it is possible to tag each accident participant with several causation factors. This also opens the possibility to not only assign causation factors to the accident causer in the sense of the law, but also to other participants involved in the accident, who may have contributed to the development of the accident. The hierarchical layout of the system and the collection of the causation factors with numerical codes allow for the possibility to code information on accident causes even if the causation factor is not known to its full extent or in full detail, given the possibility to code only those cause factors, which are known. Derived from the systematic of the analysis of human accident causes ("7 steps") and from the practical experiences of on-scene interviews of accident participants, a system was set in place, which offers the possibility to extensively record not only human causation factors in a structured form. Furthermore, the analysis of the human causation factors in such a structured way provides a tool, especially for on-scene accident investigations, to conduct the interview of accident participants effectively and in a structured way.
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.
Accidents with vulnerable road users require special attention within the road safety work because these accidents are often accompanied with severe injuries. Thus In 2006 at least 6200 Powered Two Wheeler (PTW) riders were killed in road crashes in the EU 25 representing 16% of the total number of road deaths while accounting for only 2% of the total kilometers driven. For the prevention of accidents with VRU above all the knowledge of the causes of the accidents is of special importance. This study is based on the methodology of the German In-Depth Accident Study GIDAS. Within GIDAS extensive data on various fields of accidentology are collected on-scene from road traffic accidents with injuries in the Hannover and Dresden area. Using a well defined sample plan the collected data is highly representative to the whole German situation (Brühning et al, Otte et al). The need of in-depth accident causation data in accident research led to the development of a special tool for the collection of such data called ACASS (Accident Causation Analysis with Seven Steps), which was implemented in the GIDAS methodology in 2008 and described by Otte in 2009.