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.
This study that was funded by the Research Association for Automotive Technology (FAT) develops a method for the evaluation of the placement of tanks or batteries by using the deformation frequencies in real-world accidents. Therefore, the deformations of more than 20.000 passenger cars in the GIDAS database are analysed. For each vehicle a contour of deformation is calculated and the deformed areas of the vehicles are transferred in a rangy matrix of deformation. Thereby, the vehicle is divided into more than 190.000 cells. Afterwards, all single matrices of deformation are summarized for each cell which allows representative analyses of the deformation frequencies of accidents with passenger cars in Germany. On the basis of these deformation frequencies it is possible to determine least deformed areas of all passenger cars. Furthermore, intended placements of tanks or batteries can be estimated in an early stage of development. Therefore, all vehicles with deformations in the intended tank areas can be analysed individually. Considering numerous parameters out of the GIDAS database (e.g. collision speed, kind of accident, overlap, collision partner etc.) the occurring forces can be calculated or the deformation frequency can be estimated. Furthermore, it is possible to consider the influence of primary and secondary safety systems on the deformation behaviour. The analysis of "worst case accident events" is an additional application of the calculated matrix of deformation frequency.