Sonstige
In Germany, in-depth accident investigations are carried out in the Hannover area since 1973. In 1999 a second region was added with surveys in Dresden and the surrounding area. Internationally, the acronym GIDAS (German In-Depth Accident Study) is commonly used for these surveys. Compared to many other countries, the sample sizes of the GIDAS surveys are much larger. The goal is to collect 1.000 accidents involving personal injuries per year and region. Data collection takes place by using a sampling procedure, which can be interpreted as a two-stage process with time intervals as primary units and accidents as secondary units. An important question is, to what extend these samples are representative for the target population from which they are drawn. Analyses show, for example, that accidents with persons killed or seriously injured are overrepresented in the samples compared to accidents with slightly injured persons. This means, that these data are subject to biases due to uncontrolled variation of sample inclusion probability. Therefore, appropriate weighting and expansion methods have to be applied in order to adjust or correct for these biases. The contribution describes the statistical and methodological principles underlying the GIDAS surveys with respect to sampling procedure, data collection and expansion. In addition, some suggestions regarding potential improvements of study design are made from a methodological point of view.
Impact severity is a fundamental measure for all in-depth crash investigation projects. One methodology used in the UK is based on the US Calspan software package CRASH3. The UK- in-depth crash investigation studies routinely use AiDamage3 a software package which is based on an updated version of the original CRASH3 algorithm, including enhancements to the vehicle stiffness coefficients. Real world accident-damaged vehicles are measured and their crush is correlated with a library of stiffness coefficients. These measurements are then used, along with other parameters, to calculate the crash energy and equivalent changes of velocity of the vehicles (delta-v), which is a measure of the impact severity. UK in-depth accident studies routinely validate the crash severity methodologies applied as the vehicle fleet changes. This is achieved by analysing crash test data and using the appropriate residual crush damage and other inputs to AiDamage3 and checking the program- outputs with the known crash severity parameters. This procedure checks, at least in part, the default stiffness values in the data libraries and the reconstruction methods used.
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.
The role of a national motor vehicle crash causation study-style data set in rollover data analysis
(2010)
On 1 January 2005, The National Highway Traffic Safety Administration, an agency of the United States Department of Transportation, implemented a new data collection strategy designed to assess crash avoidance technologies and report associated behavioral inputs and outcomes. The original goal was a six-year program, however, during the shortened data collection period; it proved a valuable resource for understanding a precrash environment previously obscured by forensic case investigation. Another unintended consequence was an overlap with infrastructure, roadway geometry, and design with the occupant and vehicle outcomes, by virtue of well-defined attributes. External to the collected data, supplementary information was extrapolated, by using manuals published in the United States, by the American Association of State Highway Transportation Officials and selected State Departments of Transportation, in conjunction with the National Motor Vehicle Crash Causation Study (NMVCCS). This provided a backdrop to the infrastructure framework of the rollover problem within which the occupant and vehicle outcomes were studied. If a NMVCCS-style data collection were to be implemented elsewhere, then complementary manuals produced by federal transportation officials might be consulted producing similar relationships. The current study uses NMVCCS data to describe vehicles travelling through diverse design geometries and the outcome for occupants involved in crashes within that system. Codified and extrapolated data form the basis for assessing NMVCCS and its value to the transportation safety community, as the protocols are applicable universally. The benefit in continuing a NMVCCS-style study is noted, as the interaction of roadway infrastructure and occupant protection agencies might find paths to better work together in solving the complex rollover problem using a common data-driven approach.
In den vergangenen Jahrzehnten sind einige Untersuchungsstrecken mit dem Ziel angelegt worden, verschiedene Bauweisen bei gleichen Belastungs- und Umweltbedingungen in einem direkten Vergleich bezüglich ihrer Gleichwertigkeit zu beurteilen und/oder das Verhalten von Bauweisen bei unterschiedlichen Belastungs- und Umweltbedingungen langfristig zu beobachten. Die Untersuchungen an diesen Untersuchungsstrecken dauerten einige Monate bis zu mehreren Jahren. Ziel dieser Arbeit war es, die aus den seinerzeitigen Untersuchungsergebnissen der Untersuchungsstrecken mit zum Teil jahrzehntelanger Liegedauer gezogenen bemessungsrelevanten Schlussfolgerungen zu überprüfen. Ein wesentliches Kriterium für die Auswahl von zehn Untersuchungsstrecken waren der vorhandene Datenumfang und dessen Aufbereitungsgrad. Bei einer Anzahl von zehn Strecken sind die Variationsmöglichkeiten der einzelnen oben genannten Parameter nur gering. Im Zuge der Bearbeitung des Forschungsvorhabens durch elf Forschungseinrichtungen beziehungsweise Einzelpersonen wurden für die Untersuchungsstrecken örtliche Verhältnisse, Verkehrsdaten, Wetterdaten, Schicht- und Materialdaten, Bauklassen, Einsenkungen, Deflexionen, Krümmungen, Ebenheit im Längs- und Querprofil, Fahrbahnoberflächenzustand, Zustand der seitlichen Entwässerungseinrichtungen und Erhaltungsmaßnahmen ermittelt, ausgewertet und in Teilberichten dokumentiert. Die erhobenen Daten wurden in die Datenbank der Bundesanstalt für Straßenwesen (BASt) eingespeist und stehen somit allen potentiellen Nutzern zur Verfügung. Die vorhandenen und 1992 bis 1995 erhobenen Daten wurden zur Auswertung miteinander verknüpft. Teilweise wurden Abhängigkeiten nachgewiesen und teilweise, aufgrund der geringen Streckenanzahl, nur tendentielle oder vermutete Abhängigkeiten aufgezeigt.
Due to recent years accident avoidance and crashworthiness on Austrian roads were mostly developed on national statistics and on-scene investigation respectively. Identification and elimination of black spots were main targets. In fact many fatal accidents do not occur on such black spots and black-spot investigation has reached a limit. New methods are required and therefore the Austrian Road Safety Programme was introduced by the Austrian Ministry of Transport, Innovation and Technology. The primary objective is the reduction of fatalities and severe injuries. Graz University of Technology initiated the project ZEDATU (Zentrale Datenbank tödlicher Unfälle) with the goal to identify similarities in different accident configurations. A matrix was established which categorizes risk and key factors of participating parties. Based on this information countermeasures were worked out.