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The accident research project in Dresden was founded in July 1999. To date over 6.000 crash investigations have been undertaken. About 10.000 vehicles have been documented and over 13.000 participants have been debriefed. But there is much more than this scientific success. Because of the interdisciplinary character between the medical and technical focus, the project affords an important contribution for the education of the involved students. Over 200 students of different fields of study have got experiences not only for the occupational career. This lecture describes the additional effects of the accident research project regarding the education of the students, the capacity for teamwork and learning about dealing with accident casualties.
Since its beginning in 1999, the German In-Depth Accident Study (GIDAS) evolved into the presumably leading representative road traffic accident investigation in Europe, based on the work started in Hanover in 1973. The detailed and comprehensive description of traffic accidents forms an essential basis for vehicle safety research. Due to the ongoing extension of demands of researchers, there is a continuous progress in the techniques and systematic of accident investigation within GIDAS. This paper presents some of the most important developments over the last years. Primary vehicle safety systems are expected to have a significant and increasing influence on reducing accidents. GIDAS therefore began to include and collect active safety parameters as new variables from the year 2005 onwards. This will facilitate to assess the impact of present and future active safety measures. A new system to analyse causation factors of traffic accidents, called ACASS, was implemented in GIDAS in the year 2008. The whole process of data handling was optimised. Since 2005 the on-scene data acquisition is completely conducted with mobile tablet PCs. Comprehensive plausibility checks assure a high data quality. Multi-language codebooks are automatically generated from the database structure itself and interfaces ensure the connection to various database management systems. Members of the consortium can download database and codebook, and synchronize half a terabyte of photographic documentation through a secured online access. With the introduction of the AIS 2005 in the year 2006, some medical categorizations have been revised. To ensure the correct assignment of AIS codes to specific injuries an application based on a diagnostic dictionary was developed. Furthermore a coding tool for the AO classification was introduced. All these enhancements enable GIDAS to be up to date for future research questions.
The number of injured car occupants decreases constantly. Nevertheless, they account for nearly 50% of all fatalities and about 44% of all seriously injured persons in German traffic accidents. Further reductions of casualties require multiple efforts in all parts of traffic safety. In this paper a detailed analysis of the important pre-hospital rescue phase was done. The basis for future improvements is the knowledge about injury causation of car occupants in combination with other corresponding influence factors. For that reason more than 1.200 severe (AIS3+) injuries of frontal car occupants were analyzed. For the most relevant injuries of car occupants multivariate analysis models were created to predict the probability of these injuries in a real crash scenario. In addition to the collision severity different influence factors like impact direction, seat belt usage, age of the occupant, and gender were analyzed. Furthermore, the models were checked regarding the goodness of fit and all results all results were checked concerning their robustness. The prediction models were created on the basis of 5.000 car accidents. Afterwards, the models were validated using 4.000 different car accidents. The prediction of the probability of severe injuries could be used for different applications in the field of traffic safety. One possibility is the implementation of the models in a tool for the on-the-spot diagnosis. The background for the development of such applications is the fact, that there are only limited diagnostic possibilities available at the accident scene. Nevertheless, the rescue forces have to make essential decisions like the alerting of the necessary medical experts, appropriate treatment, the type of transportation and the choice of an adequate hospital. These decisions quite often decide between life and death or influence the long-term effects of injured persons. At this point, indications of expectable injuries could help enormously. To enable even persons with limited technical knowledge to use the tool, a procedure was developed that facilitates the assumption of the given crash severity. Another important possibility for the application of the prediction models is the use for the qualification of information sent by e-call systems.
Beside numerous information about vehicles injuries and environmental data the GIDAS database contains detailed reconstruction data. This data is calculated by a reconstruction engineer who handles about 1000 accidents per year. The spectrum of one reconstruction ranges from simple crossing accidents to complex run-off accidents with rollover events. Especially for complex accident scenarios there is a large effort to design the environment of the accident scene within PC-Crash ®. To reduce the reconstruction time by maintaining the high quality of reconstruction 3D-geodata can be useful. Geodata is available for nearly every area in Germany and can be used for a fast and detailed creation of complex accident environments. In combination with the accident sketch areal images of the accident scene can be created and the participants are implemented in the new-built 3D-reconstruction environment. As a consequence, the characteristics of the terrain can be considered within the reconstruction which is especially important for run-off accidents.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.