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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 paper presents a methodology for the benefit estimation of several secondary safety systems for pedestrians, using the exceptional data depth of GIDAS. A total of 667 frontal pedestrian accidents up to 40kph and more than 500 AIS2+ injuries have been considered. In addition to the severity, affected body region, exact impact point on the vehicle, and the causing part of every injury, the related Euro NCAP test zone was determined. One results of the study is a detailed impact distribution for AIS2+ injuries across the vehicle front. It can be stated, how often a test zone or vehicle part is hit by pedestrians in frontal accidents and which role the ground impact plays. Basing on that, different secondary safety measures can be evaluated by an injury shift method concerning their real world effectiveness. As an example, measures concerning the Euro NCAP pedestrian rating tests have been evaluated. It was analysed which Euro NCAP test zones are the most effective ones. In addition, real test results have been evaluated. Using the presented methodology, other secondary safety like the active bonnet (pop-up bonnet) or a pedestrian airbag measures can be evaluated.
Each year the traffic accident research teams in Dresden and Hanover provide an in-depth investigation of approximately two thousand accidents, aggregated in the GIDAS database. To accomplish a comprehensive review of each traffic accident recorded, a sensible and thorough encoding of suffered injuries is indispensable. The Abbreviated Injury Scale by AAAM offers a valuable and handy solution to achieve this goal. However, there were a few difficulties in the use of the AIS that came up in the past, which let to necessary improvements for the utilization of the AIS 2005 for GIDAS.
The changed focus in vehicle safety technology from secondary to primary safety systems need to evolve new methods to investigate accidents, high critical, critical and normal driving situations. Current Naturalistic Driving Studies mostly use vehicles that are highly equipped with additional measuring devices, video cameras, recording technology, and sensors. These equipped fleets are very expensive regarding the setup and administration of the study. Due to the great rarity of crashes it is additionally necessary to have a high distribution and a homogeneous distribution of subject groups. At the end all these facts are leading to a very expensive study with a manageable number of data. Smartphones are becoming more and more popular not only for younger people. Contrary to traditional mobile phones they are mostly equipped with sensors for acceleration and yaw rates, GPS modules as well as cameras in high definition resolution. Additionally they have high-performance processors that enable the execution of CPU-intensive tools directly on the phone. The wide distribution of these smartphones enables researchers to get high numbers of users for such studies. The paper shows and demonstrates a software app for smartphones that is able to record different driving situations up to crashes. Therefore all relevant parameter from the sensors, camera and GPS device are saved for a given duration if the event was triggered. The complete configuration is independently adjustable to the relevant driver and all events were sent automatically to the research institute for a further process. Direct after the event, interviews with the driver can be done and important data regarding the event itself are documented. The presentation shows the methodology and gives a demonstration of the working progress as well as first results and examples of the current study. In the discussion the advantages of this method will be discussed and compared with the disadvantages. The paper shows an alternative method to investigate real accident and incident data. This method is thereby highly cost efficient and comparable with existing methods for benefit estimation.
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 sequence of accident events can be classified by three essential phases, the pre-crash-sequence, the crash-sequence and the post-crash-sequence. The level of reliability of the information in the GIDAS-database (German In Depth Accident Study) is provided predominantly on the passive side. The period to evaluate active safety systems begins already in the pre-crash-sequence. The assessment of the potential of sensor- or communication-based active safety systems can only be accomplished by a detailed analysis of the pre-crash-phase. Hence the necessity to analyze the early period of the accident event in detail arises. This is possible with the help of the digital sketches of the accident site and the simulation of the accident by a simulation method of the VUFO GmbH. After simulating the pre-crash scenario it is possible to generate additional and standardized data to describe the pre-crash-sequences of an accident in a very high detail. These data are documented in a second database called the GIDAS Pre-Crash-Matrix (PCM). The PCM contains various tables with all relevant data to reproduce the pre-crash-sequence of traffic accidents from the GIDAS database until 5 seconds before the first collision. This includes parameters to describe the environment data, participant data and motion or dynamic data. This paper explains the creation of the PCM, the simulation itself and the contents and structure of the PCM. With this information of the pre-crash-sequence for various accident scenarios an improved benefit estimation and development of active safety systems can be made possible.
Aim of the study was to evaluate the protective effect of bicycle helmets particularly considering injuries to the head and to the face. Accidents with the participation of bicyclists which occurred from 2000 to 2007 were chosen from GIDAS. We observed that injuries to the head and face were more severe in the group of non-helmeted riders. There seems to be no significant difference in injuries with AIS 3-6. Altogether 26 cyclists were killed. 2 of them wore a helmet (1% of helmeted cyclists), 24 did not (1% of non-helmeted cyclists). Only one killed rider (without helmet) did not suffer from polytrauma (only head injuries recorded). The findings seem to support the thesis of a preventive effect of the bicycle helmet, however the two groups are different in their characteristics related to riding speed. Necessarily we need a multivariate model to evaluate the effect of helmets.
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.
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.
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.