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- 2015 (4) (entfernen)
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- Abteilung Fahrzeugtechnik (4) (entfernen)
The project UR:BAN "Cognitive assistance (KA)" aims at developing future assistance systems providing improved performance in complex city traffic. New state-of-the-art panoramic sensor technologies now allow comprehensive monitoring and evaluation of the vehicle environment. In order to improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is the evaluation and prediction of their behaviour and actions. The objective of subproject "WER" is development support by providing quantitative estimates of traffic collisions at the very start and predict potential in terms of optimized accident avoidance and reduction of injury severity. For this purpose an integrated computer simulation toolkit is being devised based on real world accidents (GIDAS as well as video documented accidents), allowing the prediction of potential effectiveness and future benefit of assistance systems in this accident scenario. Subsequently, this toolkit may be used for optimizing the design of implemented assistance systems for improved effectiveness.
The EVERSAFE project addressed many safety issues for electric vehicles including the crash and post-crash safety. The project reviewed the market shares of full electric and hybrid vehicles, latest road traffic accident data involving severely damaged electric vehicles in Europe, and identified critical scenarios that may be particular for electric vehicles. Also, recent results from international research on the safety of electric vehicles were included in this paper such as results from performed experimental abuse cell and vehicle crash tests (incl. non-standardized tests with the Mitsubishi i-MiEV and the BMW i3), from discussions in the UN IG REESS and the GTR EVS as well as guidelines (handling procedures) for fire brigades from Germany, Sweden and the United States of America. Potential hazards that might arise from damaged electric vehicles after severe traffic accidents are an emerging issue for modern vehicles and were summarized from the perspective of different national approaches and discussed from the practical view of fire fighters. Recent rescue guidelines were reviewed and used as the basis for a newly developed rescue procedure. The paper gives recommendations in particular towards fire fighters, but also to vehicle manufacturers and first-aiders.
In the paper it is investigated to what extend one can extrapolate the detailed accident database GIDAS (German In-Depth Accident Study), with survey area Hanover and Dresden region, to accident behavior in other regions and countries within Europe and how such an extrapolation can be implemented and evaluated. Moreover, it is explored what extent of accident data for the target country is necessary for such an extrapolation and what can be done in situations with sparse and low accident information in a target region. It will be shown that a direct transfer of GIDAS injury outcomes to other regions does not lead to satisfactory results. But based on GIDAS and using statistical decision tree methods, an extrapolation methodology will be presented which allows for an adequate prediction of the distribution of injury severity in severe traffic accidents for European countries. The method consists essentially of a separation of accidents into well-described subgroups of accidents within which the accident severity distribution does not vary much over different regions. In contrast the distribution over the various subgroups of accidents typically is rather different between GIDAS and the target. For the separation into the subgroups meaningful accident parameters (like accident type, traffic environment, type of road etc.) have been selected. The developed methodology is applied to GIDAS data for the years 1999-2012 and is evaluated with police accident data for Sweden (2002 to 2012) and the United Kingdom (2004 to 2010). It is obtained that the extrapolation proposal has good to very good predictive power in the category of severe traffic accidents. Moreover, it is shown that iterative proportional fitting enables the developed extrapolation method to lead to a satisfactory extrapolation of accident outcomes even to target regions with sparse accident information. As an important potential application of the developed methodology the a priori extrapolation of effects of (future) safety systems, the operation of which can only be well assessed on the basis of very detailed GIDAS accident data, is presented. Based on the evaluation of the presented extrapolation method it will be shown that GIDAS very well represents severe accidents, i.e. accidents with at least one severely or fatally injured person involved, for other countries in Europe. The developed extrapolation method reaches its limits in cases for which only very little accident information is available for the target region.
Abbiegeunfälle mit Kollisionen zwischen rechtsabbiegenden Güterkraftfahrzeugen und Fahrrädern haben in der Regel schwerwiegende Folgen für den ungeschützten Verkehrsteilnehmer. In der Vergangenheit wurde durch eine steigende Anzahl von Spiegeln das individuelle Sichtfeld des Lkw-Fahrers vergrößert und die Sicherheit für ungeschützte Verkehrsteilnehmer durch den Seitenunterfahrschutz verbessert. Da Abbiegeunfälle trotz der Vielzahl an Spiegeln auch heute noch geschehen, gleichzeitig aber Fahrerassistenzsysteme Einzug in viele Fahrzeugklassen gehalten haben, liegt es nahe, derartige Systeme für die Verhinderung von Abbiegeunfällen zu nutzen. Um entsprechende Systementwicklungen fördern zu können oder aber auch Systeme vorschreiben zu können, sind Anforderungen und passende Testmethoden für Abbiegeassistenzsysteme erforderlich. Ziel der BASt war es, solche Anforderungen und ein mögliches Testverfahren hierfür zu entwickeln. Ausgehend von Analysen des Unfallgeschehens wurden charakteristische Parameter und Begleitumstände von Unfällen zwischen Fahrrädern und rechtsabbiegenden Lkw identifiziert. Aus fahrdynamischen Überlegungen folgt bei den gegebenen Parametern, dass nur eine frühe, aber niederschwellige Fahrerinformation eine wirkungsvolle Assistenzfunktion zur Verhinderung der Unfälle sein kann. Für automatische Bremsungen gibt es bisher noch zu wenig Erfahrungen im Feld, und klassische, hochschwellige, aber sehr spät erfolgende Warnsignale würden durch die dann noch verstreichende Reaktionszeit keine rechtzeitige Bremsung des Lkw-Fahrers mehr hervorrufen. Basierend auf dem identifizierten Parameterraum, der zum komfortablen Anhalten erforderlichen Zeit und einem geeigneten Kinematikmodell lassen sich die räumlichen Bereiche um den Lkw definieren, in dem eine Umfelderkennung den Fahrradfahrer detektieren können muss, damit das Informationssignal durch das Assistenzsystem an den Lkw-Fahrer rechtzeitig ausgegeben wird. Aktuell wird davon ausgegangen, dass ein Abbiegeassistenzsystem, das die hier beschriebenen Prüfungen besteht, einen sehr positiven Einfluss auf das Unfallgeschehen zwischen rechtsabbiegenden Lkw und Fahrrädern haben wird.