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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.
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.
Sowohl die Zahl der im Straßenverkehr Getöteten wie auch die der Schwerverletzten sind nach Angaben der amtlichen Statistiken in Deutschland seit Jahren rückläufig. Die Gruppe der Schwerverletzten ist allerdings sehr heterogen und umfasst alle Unfallopfer, die für mindestens 24 Stunden in einem Krankenhaus behandelt wurden. Die vorliegende Untersuchung versucht, mit Hilfe von Daten des Traumaregisters der Deutschen Gesellschaft für Unfallchirurgie (DGU) die Frage zu beantworten, ob auch bei den besonders schwer verletzten Verkehrsunfallopfern ein Rückgang der Zahlen zu beobachten ist. Dazu wurden "schwerstverletzte" Patienten definiert als solche, die im Injury Severity Score (ISS) mindestens 9 Punkte erreicht haben und zudem intensivmedizinisch behandelt werden mussten. Der Zeitraum der Untersuchung umfasst zehn Jahre von 1997 bis 2006, der für einige Fragestellungen zusätzlich in zwei je 5-jährige Phasen unterteilt wurde. Ab 2002 (Phase 2) ist auch eine separate Auswertung für Fahrrad- und Motorradfahrer möglich. Die erste Fragestellung richtete sich auf die Veränderung der Anzahl schwerstverletzter Verkehrsunfallopfer über die Zeit. Dafür wurden die Daten von über 11.000 Patienten aus 67 verschiedenen Kliniken betrachtet. Pro Klinik wurde ein Durchschnittswert für die Anzahl von Verkehrsunfallopfern bestimmt, der dann mit der tatsächlich beobachteten Zahl verglichen wurde. Im Ergebnis zeigte sich, dass die relativen Abweichungen vom Durchschnitt insgesamt nur etwa -±10% betragen und dass kein deutlicher Trend einer Abnahme oder Zunahme der Schwerstverletztenzahlen in den vergangenen 10 Jahren erkennbar ist. In der zweiten Fragestellung wurde untersucht, ob und wie stark ein Rückgang der Letalität zu einem Anstieg der Schwerstverletztenzahlen geführt haben könnte. Es konnte gezeigt werden, dass in den letzten beiden Jahren deutlich weniger Patienten im Krankenhaus verstorben sind, als dies nach ihrer Prognose zu erwarten gewesen wäre. Dieser Rückgang der Letalitätsrate von absolut bis zu 5 (in 2006: Prognose 18% versus beobachtet 13%) trägt damit auch zu einer Zunahme bei der Zahl der Schwerstverletzten bei. Zur Abschätzung der Prognose wurde ein im Traumaregister entwickeltes und validiertes Scoresystem (RISC) eingesetzt. In der letzten Fragestellung sollte geklärt werden, ob sich das Verletzungsmuster bei den Schwerstverletzten in den vergangenen zehn Jahren und abhängig von der Art der Verkehrsteilnahme verändert hat. Insgesamt konnte gezeigt werden, dass der relative Anteil der Autofahrer rückläufig war, von 60% auf 50%. Bei den verletzten Körperregionen zeigt das Schädel-Hirn-Trauma den deutlichsten Rückgang von 69 % auf 60% insgesamt. Dieser Trend ist bei allen Verkehrsbeteiligten erkennbar. Lediglich Verletzungen der Wirbelsäule werden häufiger gesehen, was aber auch ein Effekt der verbesserten CT-Diagnostik sein kann, zum Beispiel beim Ganzkörper-CT. Je nach Art der Verkehrsbeteiligung zeigen sich sehr unterschiedliche Verletzungsmuster. Verletzungen des Kopfes sind bei Radfahrern und Fußgängern dominierend (über 70%), während Motorradfahrer hier die günstigsten Raten zeigen (45%). Motorrad- und Autofahrer haben die höchsten Raten für Verletzungen des Brustkorbs und im Bauchraum, bedingt durch die im Mittel höheren einwirkenden Kräfte auf den Körper. Insgesamt lassen sich die Daten des DGU-Traumaregisters gut nutzen, um typische Verletzungsmuster zu beschreiben und um relative Veränderungen bei der Zahl der Schwerstverletzten über die Zeit nachzuweisen. Beobachtungszeiträume von zehn Jahren und mehr, wie im vorliegenden Fall, ermöglichen auch aktuelle Trendaussagen. Epidemiologische Aussagen wie in den amtlichen Statistiken sind aber nur sehr eingeschränkt möglich, da das Traumaregister bisher nur auf freiwilliger Basis Daten sammelt.
Crash involvement studies using routine accident and exposure data : a case for case-control designs
(2009)
Fortunately, accident involvement is a rare event: the chance of an individual road user trip to end up in a crash is close to zero. Thus, according to general epidemiological principles one can expect the case-control study design to be especially suitable for quantifying the relative risk (odds ratio) of accident involvement of road users with a certain risk factor as compared to road users that do not have this characteristic. Ideally, of course, the database for such a case-control study should be established by drawing two independent random samples of cases (accidental units) and controls (nonaccidental units), respectively. If, however, special data collection is not an option, it is nevertheless possible to analyze routine accident and exposure data under a case-control design in order to fully exploit the information contained in already existing databases. As a prerequisite, accident and exposure data from different sources are to be combined in a single file of micro or grouped data in a way consistent with the case-control study design. Among other things, the proposed methodological approach offers the possibility to use in-depth data of the GIDAS type also in investigations of active vehicle safety by combining this data with appropriate vehicle trip data collected in mobility surveys.
Who doesn't wear seat belts?
(2009)
Using real world accident data, seat belts were estimated to be 61% effective at preventing fatalities, and 32% effective at preventing serious injuries. They were most effective for drivers with an airbag. Seat belts were estimated as having prevented 57,000 fatalities and 213,000 seriously injured casualties in the UK since 1983. Seat belt legislation was estimated to have prevented 31,000 fatalities and 118,000 seriously injured casualties. A future increase in effective seat belt wearing rate (which takes into account seating position) in the UK from 92.5% to 93% may prevent casualties valued at a societal cost of over -£18 million per year. To target a seat belt campaign, the question "who doesn"t wear seat belts?" must be answered. Seat belt wearing rates and the number of unbelted casualties were analysed. It was primarily young adult males who didn"t wear seat belts, and they made up the majority of unbelted fatalities and seriously injured casualties.
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.
A set of recommendations for pan-European transparent and independent road accident investigations has been developed by the SafetyNet project. The aim of these recommendations is to pave the way for future EU scale accident investigation activities by setting out the necessary steps for establishing safety oriented road accident investigations in Member States. This can be seen as the start of the process for establishing road accident investigations throughout Europe which operate according to a common methodology. The recommendations propose a European Safety Oriented Road Accident Investigation Programme which sets out the procedures that need to be put in place to investigate a sample of every day road accidents. They address four sets of issues; institutional addressing the characteristics of the programme; operational describing the conditions under which data isrncollected; data storage and protection; and reports, countermeasures and the dissemination of data.rn
Nowadays, traffic accidents are recorded in historical databases. Regarding the huge quantity of data, the use of data mining tools is essential to help Experts, for automatically extracting relevant information in order to establish and quantify relations between severity and potential factors of accidents. An innovative approach is here proposed for an in depth investigation of real world accidents data base. Mutual information ratio based on conditional entropies is used to quantity the association strength between an accident outcome descriptor (injury severity) and other potential association factors. Information theoretic methods help to select automatically groups of factors mostly responsible of the severity of accident.
One goal of the assessment of the crashworthiness of passenger cars is to characterize the potential of injury outcome to occupants of cars involved in an accident. This can be achieved by the help of an index that puts the number of injured occupants of passenger cars in relation to the number of cars involved in an accident. As a consequence, this index decreases with a lower potential of injury and rises with a higher number of injuries while assuming a fixed number of accidents. Another index is introduced that uses an economical weighting of each injury level. The consequential injury costs are calculated using the average economical costs for lightly, severely and fatally injured persons. The calculation of the safety indices is based on an anonymized sample of accident data provided by the Federal Statistical Office. An index of Mercedes passenger car drivers depending on the year of registration between 1991 and 2006 is compared to the index of drivers of cars of other makes within the same range of registration years.
A lack of representative European accident data to aid the development of safety policy, regulation and technological advancement is a major obstacle in the European Union. Data are needed to assess the performance of road and vehicle safety and is also needed to support the development of further actions by stakeholders. This short-paper describes the process of developing a data collection and analysis system designed to partly fill these gaps. A project team with members from 7 countries was set up to devise appropriate variable lists to collect fatal crash data under the following topic levels: accident, road environment, vehicle, and road user, using retrospective detailed police reports (n=1,300). The typical level of detail recorded was a minimum of 150 variables for each accident. The project will enable multidisciplinary information on the circumstances of fatal crashes to be interpreted to provide information on a range of causal factors and events surrounding the collisions.