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Small overlap frontal crashes are defined by a damage pattern with most of the vehicle deformation concentrated outboard of the main longitudinal structures. These crashes are prominent among frontal crashes resulting in serious and fatal injuries, even among vehicles that perform well in regulatory and consumer information crash tests. One of the critical aspects of understanding these crashes is knowing the crash speeds that cause the types of damage associated with serious injuries. Laboratory crash tests were conducted using 12 vehicles in three small overlap test conditions: pole, vehicle-to-vehicle collinear, and vehicle-to-vehicle oblique (15-degree striking angle). Field reconstruction techniques were used to estimate the delta V for each vehicle, and these results were compared with actual delta V values based on vehicle accelerometer data. Estimated delta Vs were 50% lower than actual values. Velocity change estimates for small overlap frontal crashes in databases such as NASS-CDS significantly underestimate actual values.
Causation patterns and data collection blind spots for fatal intersection accidents in Norway
(2010)
Norwegian fatal intersection accidents from the years 2005-2007 were analysed to identify any causation patterns among their underlying contributing factors, and also to evaluate whether the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to perform causation pattern analysis. A total of 28 fatal accidents were analysed. Details on crash contributing factors for each driver in each crash were first coded using the Driving Reliability and Error Analysis Method (DREAM), and then aggregated based on whether the driver was going straight or turning. Analysis results indicate that turning drivers to a large extent are faced with perception difficulties and unexpected behaviour from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers going straight on the other hand have less perception difficulties. Instead, their main problem is that they largely expect turning drivers to yield. When this assumption is violated, they are either slow to react or do not react at all. Contributing factors often pointed to in literature, e.g. high speed, drugs and/or alcohol and inadequate driver training, played a role in 12 of 28 accidents. While this confirms their prevalence, it also indicates that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, information on blunt end factors (those more distant in time/space, yet important for the development of events) was more limited than information on sharp end factors (those close in time/space to the crash). A possible explanation is that analysts may view some blunt end factors as event circumstances rather than contributing factors in themselves, and therefore do not report them. There was also an asymmetry in terms of reported obstructions to view due to signposts and vegetation. While frequently reported as contributing for turning drivers, they were rarely reported as contributing for their counterparts in the same accidents. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver legally held liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator mindset needs addressing to avoid future bias in crash investigation reports.
Recent findings from real-world accident data have shown that fatality risks for pedestrians are substantially lower than generally reported in the traffic safety literature. One of the keys to this insight has been the large and random sample of car-to-pedestrian crashes available in the German In-Depth Accident Study (GIDAS). Another key factor has been the proper use of weight factors in order to adjust for outcome-based sampling bias in the accident data. However, a third factor, a priori of unknown importance, has not yet been properly analysed. This is the influence of errors in impact speed estimation. In this study, we derived a statistical model of the impact speed errors for pedestrian accidents present in the GIDAS database. The error model was then applied to investigate the effect of the estimation error on the pedestrian fatality risk as a function of car impact speed. To this end, we applied a method known as the SIMulation-EXtrapolation (SIMEX) method. It was found that the risk curve is fairly tolerant to some amount of random measurement error, but that it does become flattened. It is therefore important that the accident investigations and reconstructions are of high quality to assure that systematic errors are minimised and that the random errors are under control.
The NHTSA-sponsored Crash Injury Research and Engineering Network (CIREN) has collected and analyzed crash, vehicle damage, and detailed injury data from over 4000 case occupants who were patients admitted to Level-I trauma centers following involvement in motor vehicle crashes. Since 2005, CIREN has used a methodology known as "BioTab" to analyze and document the causes of injuries resulting from passenger vehicle crashes. BioTab was developed to provide a complete evidenced-based method to describe and document injury causation from in-depth crash investigations with confidence levels assigned to the causes of injury based on the available evidence. This paper describes how the BioTab method is being used in CIREN to leverage the data collected from in-depth crash investigations, and particularly the detailed injury data available in CIREN, to develop evidence-based assessments of injury causation. CIREN case examples are provided to demonstrate the ability of the BioTab method to improve real-world crash/injury data assessment.
Ziel des Forschungsprojektes war die quantitative Vorausschätzung des Straßenverkehrsunfallgeschehens der Jahre 2015 und 2020 in Deutschland mit Hilfe eines eigens entwickelten Prognoseverfahrens. Das Verfahren sollte eine größtmögliche Differenzierung des zukünftigen Unfallgeschehens nach Schweregrad, Art der Verkehrsbeteiligung und Alter der Verkehrsteilnehmer erlauben. Das Modell sollte grundsätzlich in der Lage sein, Ursache - Wirkungszusammenhänge differenzierter als in herkömmlichen Ansätzen der Zeitreihenanalyse und deren Trendfortschreibung abzubilden. Den Prognosehorizont bilden die Jahre 2015 und 2020. Im Rahmen des vorliegenden Projekts erfolgte für Deutschland erstmals eine Prognose der Unfall- und Verunglücktenzahlen über eine Risikoanalyse maßgebender Unfallkonstellationen. Dabei wurde sowohl nach Ortslagen, Unfallbeteiligten und Alter der Verkehrsteilnehmer unterschieden. Mit Hilfe des vorgestellten Prognosemodells lässt sich der künftige Grad der Straßenverkehrssicherheit differenziert beurteilen. Auswirkungen der sich ändernden Rahmenbedingungen auf das Unfallgeschehen werden sowohl auf der Ebene der Unfallentstehung als auch auf der Ebene der Unfallschwere berücksichtigt. Dabei kann insbesondere der Einfluss aus Demografie und sich verändernder Zugangsvoraussetzungen zu Verkehrsmitteln auf das Unfallgeschehen abgebildet werden. Der vorgestellte erste Entwicklungsstand des Modells bietet daher bereits sehr gute Möglichkeiten, Wirkungsanalysen bei veränderten Einflussgrößen durchzuführen. Das Unfallprognosemodell wurde modular aufgebaut. Dadurch konnte eine logische und hierarchische Modellstruktur realisiert werden. In der Folge werden die einzelnen Module im Gesamtmodell sequentiell durchlaufen, sind in sich geschlossen und folgen eigenen Berechnungsvorschriften. Eine Umsetzung des Modells erfolgte auf Basis verknüpfter Excel-Dateien mit Hilfe von VBA-Makros. Hierbei wurde auf eine stark getrennte Struktur der einzelnen Berechnungsschritte Wert gelegt, um die einzelnen Dateien übersichtlich und nachvollziehbar zu gestalten. Gleichzeitig erfüllt das Modell die Forderung einer größtmöglichen Variabilität. So können sowohl geänderte Eingangsdaten zugrundegelegt werden als auch die Auswahl der differenzierten Trendberechnung beliebig getroffen werden. Im Ergebnis ist auf Basis der getroffenen Annahmen, der historischen Entwicklung und der konstellationenfeinen Fortschreibung der Risikofaktoren ein deutlicher Rückgang der Unfall- und Verunglücktenzahlen in Deutschland für den Prognosezeitraum gegenüber 2006 zu erwarten. Bei den Unfällen mit Personenschaden ist bis 2020 mit einer Abnahme um nahezu 30 % zu rechnen, bei den Verunglückten kann von einer Reduzierung um 13 % ausgegangen werden. Die Zahl getöteter Personen sinkt dabei voraussichtlich von ca. 5.100 Personen (2006) auf 2.700 Personen (2020). In Bezug auf die Schwerverletzten ist im gleichen Zeitraum mit einem Rückgang um ca. 33.000 Personen zu rechnen (2006: 74.500 Personen). Ebenso sinkt gegenüber dem Analysejahr 2006 die Anzahl Leichtverletzter um etwa 6 % auf etwa 326.000 Personen. Die Rückgänge der Verunglücktenzahlen liegen zwischen 2006 und 2015 sowie zwischen 2015 und 2020 zahlenmäßig auf einem vergleichbaren Niveau (55.000 bzw. 58.000 V). Somit wird etwa die Hälfte der Gesamtrückgänge im Prognosezeitraum allein in den letzten fünf Jahren der insgesamt fünfzehnjährigen Zeitspanne erreicht.
From literature well-known analyzes on risks, hazards and causes of accidents of older drivers are amended by the present study in which a comparison of the specific features of accident causes of older car drivers (older than 60 years) and of younger car drivers (under 25 years) is conducted. Mainly the question is pursued if specific errors, mistakes and lapses are predominant in the two different age groups. The analysis system ACAS (Accident Causation Analysis System) used hereby consists of a sequential system of accident causation factors from the human, the technical and the infrastructural field, whereupon for this study the influence of the human features on the accident development in two different age groups is of interest. ACAS is both an accident model and an analysis and classification system, which describes the human participation factors of an accident and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. In five steps (categories) of a logical and temporal sequence the hierarchical system makes human functions and processes as determinants of accident causes identifiable. The methodology specifically focuses on the use in so-called "In-Depth" and "On-Scene" investigation studies. With the help of the system for each accident participant one or more of five hypotheses of human cause factors are formed and then specified by appropriate verification criteria. These hypotheses in turn are further specified by indicators in such manner that the coding of the causation factors by a code system meets the needs of database processing and are accessible to a quantitative data analysis. The first results of the descriptive comparison of the two age groups concern mainly differences in the functional levels "information admission/perception" (where the elderly drivers have more difficulties than the young ones) and "information processing/evaluation" (where the younger drivers show more problems). Concerning the cognitive function of "planning" the group of younger drivers seems to be more often involved in an accident because of excessive speed.
The main objective of EC CASPER research project is to reduce fatalities and injuries of children travelling in cars. Accidents involving children were investigated, modelling of human being and tools for dummies were advanced, a survey for the diagnosis of child safety was carried out and demands and applications were analysed. From the many research tasks of the CASPER project, the intention of this paper is to address the following: • In-depth investigation of accidents and accident reconstruction. These will provide important points for the injury risk curve, in order to improve it. Different accident investigation teams collected data from real road accidents, involving child car passengers, in five different European countries. Then, a selection of the most appropriate cases for the injury risk curve and the purposes of the project was made for an in-depth analysis. The final stage of this analysis was to conduct an accident reconstruction to validate the results obtained. The in-depth analysis included on-scene accident investigation, creating virtual simulations of the accident/possible reconstruction, and conducting the reconstruction. In the cases of successful reconstructions, new points were introduced to the injury risk curves. Accident reconstructions of selected cases were carried out in test laboratories as the next step following in-depth road accident investigation. These cases were reconstructed using similar child restraint systems (CRS) and the same type make and model as in the real accidents. Reconstructing real cases has several limitations, such as crash angle, cars" approximation paths and crash speed. However, a few changes and applications on the testing conditions were applied to reduce the limitations and improved the representations of the real accidents. After conducting the reconstructions, a comparison between the deformations of the cars on the real accident and the vehicles from the reconstructions was made. Additionally, a correlation between the data captured from the dummies and the injury data from the real accident was sought. This finalises an in-depth analysis of the accident, which will provide new relevant points to the injury risk curve. The CASPER project conducted a large research programme on child safety. On technical points, a promising research area is the developing injury risk curves as a result of in-depth accident investigations and reconstructions. This abstract was written whilst the project was not yet finished and final results are not yet known, but they will be available by the time of the conference. All the works and findings will not necessarily be integrated in the industrial versions of evaluation tools as the CASPER project is a research program.
Injuries in motorbike accidents in correlation with protective clothes and mechanism of the accident
(2013)
This study deals with a possible connection between safety clothing / accident mechanism and injury severity in a state-wide traffic accident investigation with focus on light and small motorbike-involvement for accidents in the area of the Saarland in which the persons riding the bike have been injured or killed. An interdisciplinary team of medical scientists and engineers collected the medical and technical data as well as all the relevant traces of the accident on scene and in time. During twenty months of data collection a total of 401 cases could be gathered. Grave injuries were more common for the group of heavier motorcycles (>125 ccm). Motorcyclists had been polytraumatized only in the group where the accident was connected with a collision. Significant correlation between protective clothes and injury severity could only be found for protective gloves and protective trousers. The knowledge about mechanism of the accident, protective clothes and severity of injuries can be helpful for the improvement of road and motorcyclists' safety.
This study analyses no.39 cases in which n.41 motorcyclists were fatally injured, or 36% of total motorcycle fatalities in Northern Ireland between 2004 and 2010 (n.114). There were n.17 cases (43.6%) where the actions of another vehicle driver caused the collision, in thirteen of these cases the motorcycles had their lights switched on. The remaining n.22 collisions (56.4%) were due to the actions of the motorcyclist. In the approach to the collision scene, there were n.13 cases (31.7%) in which the approach was a right hand bend and in n.8 (19.5%) cases, the approach was a left hand bend. In the remaining n.18 (43.9%) cases, the approach was a straight road. Of the n.17 (41.4%) motorcycles that slid after falling, n.10 (24.4%) fell onto their right side and the remaining n.7 (17.1%) fell onto their left side. The information from this study identifies primary and contributory causes of motorcycle collisions.
The objective of the study is to measure the risk of pedestrian and bicyclist in urban traffic through an analysis of real-world accident data. The kinematics and injury mechanisms for both pedestrian and bicyclists are investigated to find the correlation of injury risks with injury related parameters. For this purpose, firstly 338 cases are selected as a sample from an IVAC accident database based on the In-depth Investigation of Vehicle Accident in Changsha of China. A statistic measurement of the fatality and serious injury risks with respect to impact speed was carried out by logistic regression analysis. Secondly, 12 pedestrian and 12 bicyclist accidents were further selected for reconstruction with MADYMO program. A comparative analysis was conducted based on the results from accident analysis and computer reconstructions for the injury risk, head impact conditions and dynamic response of pedestrians and bicyclists. The results indicate that bicyclists suffered lower risks of severe injuries and fatalities compared with pedestrians. The risks of AIS 3+ injury and fatality are 50% for pedestrians at impact speeds of 53.2 km/h and 63.3 km/h, respectively, while that for bicyclists at 62.5 km/h and 71.1 km/h, respectively. The findings could have a contribution to get a better understanding of pedestrians" and bicyclists" exposures in urban traffic in China, and provide background knowledge to generate strategies for pedestrian protection.