81 Unfallstatistik
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Die Bundesanstalt für Straßenwesen (BASt) bringt zum Ende jeden Jahres eine Prognose der Unfall- und Verunglücktenzahlen des noch laufenden Jahres heraus, um so über die Entwicklung der Verkehrssicherheit in Deutschland Bilanz ziehen zu können. Dabei wird das Unfallgeschehen nach dem Schweregrad der Konsequenzen, der Ortslage sowie Alter und Art der Verkehrsbeteiligung der Verunglückten in 27 Zeitreihen unterteilt. Zu diesem Zeitpunkt sind die Daten lediglich für die ersten acht oder neun Monate erhältlich. Um Bilanz zu ziehen, werden die Anzahlen der letzten drei oder vier Monate prognostiziert. Gesamtziel des hier beschriebenen Forschungsvorhabens ist die Optimierung der jährlichen Unfallprognosen durch Anwendung von strukturellen Zeitreihenmodellen, bei denen die Vorhersagen aus dem Trend der vorliegenden Monate, und der Dynamik der vorhergehenden Jahre abgeleitet werden. Um dem Einfluss der Witterungsverhältnisse Rechnung zu tragen, werden dabei meteorologische Variablen in das Vorhersagemodell aufgenommen. Um die Modelle zu testen, werden die endgültigen Daten der letzten 15 Jahre jeweils aus den vorläufigen Daten der ersten Monate vorhergesagt und mit den tatsächlich beobachteten endgültigen Unfall- und Verunglücktenzahlen verglichen. Die Resultate zeigen, dass im Vergleich zu den bisherigen Vorhersagen mithilfe der hier vorgestellten Modelle die Vorhersagen für 25 der 27 Reihen präziser werden. Lediglich zwei Reihen zeigen einen leichten Anstieg des Vorhersagefehlers. Beim Vergleich von Modellen mit und ohne meteorologischen Variablen zeigt sich, dass 23 der 27 Reihen besser vorhergesagt werden können, wenn man das Wetter berücksichtigt. Neben der verbesserten Vorhersage ermöglicht die Aufnahme der Wettervariablen auch eine Einschätzung, wie groß der Einfluss der Witterungsgegebenheiten auf das Unfallgeschehen ist. Es zeigt sich also, dass die Anwendung von strukturellen Zeitreihenmodellen und die Berücksichtigung von meteorologischen Variablen zu einer deutlichen Verbesserung der Vorhersagegenauigkeit führen. Die Verbesserung der Vorhersagen durch die Aufnahme von Wettervariablen bestätigt nochmals den Einfluss der Witterungsumstände auf das Unfallgeschehen.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.
The paper gives an overview of the recent (mostly 2012) figures of killed bus/coach occupants (drivers and passengers) in 27 Member States of the European Union as reported by CARE. The Evolution of the figures of bus/coach occupants killed in road accidents urban, rural without motorway and on motorways from 1991 to 2010 in 15 Member States of the EU supplements this information. More detailed are the figures reported for Germany by the Federal Statistics. The paper displays long-term evaluations (1957 to 2012) for killed, seriously and slightly injured occupants in all kinds of buses/coaches. Midterm evaluations (1995 to 2012) of the figures of fatalities and casualties are displayed for different busses according to their identification of road using as coaches, urban buses, school buses, trolley buses and "other buses". To be able to compare the evolutions of the safety of vehicle occupants it is customary to use different risk indicators. Calculations and illustrations for three often used indicators with their development over time are given: fatalities, seriously injured and slightly injured per 100,000 vehicles registered, per 1 billion (109) vehicle-kilometres travelled and per 1 billion (109) person-kilometres. These indicators are shown for occupants of cars, goods vehicles and buses/coaches. For the period from 1957 until 2012 it is obvious, that for all three vehicle categories analysed there was a clear long-term trend towards more occupant safety in terms of casualties per vehicles registered and per vehicle mileage. This was most significant for car occupants but it can be seen for bus/coach occupants and goodsvehicle occupants as well. Figures of killed occupants and of casualties related to person-kilometres are calculated and displayed for the shorter period 1995 to 2012. Here it becomes obvious that the bus/coach is still the safest mode of transport for the occupants of road vehicles. Graphs for the casualty risk indices still show significantly higher risks for car occupants despite the corresponding curve moved sustainable downwards. It is remarkable, that the risks of being killed or injured for the occupants of urban buses is growing whereas the corresponding risk for the occupants of coaches in line traffic tends downwards. The article ends with a short comparison and discussion of the risk indicators which are actually published for the occupants (driver and passengers) of cars and the passengers of buses/coaches, railroads, trams and airplanes. The interpretation of such information depends on the perception and it seems that for a complete view not only one indicator should be used and the evolutions of the indicator values during longer periods (as displayed with examples in the paper) should also be taken into account.
Enhanced protection of pedestrians and cyclists remains on the focus. Besides infrastructural and behavioral aspects it is necessary to exploit technical solutions placed on motorized vehicles. Accident research needs reliable data as well as national road accident statistics. Changing the view on seriously injured road users is one of the challenges which will substantially contribute to the optimization on future traffic safety. The missing accuracy in the definition of personal injury has a detrimental effect on making cost efficient road safety policy which is not only focused on fatal accidents. The European commission requested that, starting in 2015, all EU member states provide more detailed data on the injury status of road casualties, with special regard to the group of seriously injured. Conventional accident data will always be essential. But to obtain detailed data about driver behavior in real traffic situations further data sources are required. These could be EDR data, data from electronic control units, data from traffic surveys and traffic counting, naturalistic diving studies and field operational tests. Gaining insight into normal as well as critical driver behavior will enable accident researchers to deduct functions estimating the increase or decrease of accident risk associated with certain behaviors or vehicle functions. Also with view to the introduction of highly automated driving functions in the future such data is urgently needed. Computer simulation based tools to estimate the benefits of active safety systems are another step on the way towards the safety assessment of automated driving. It is now the duty of the scientific community to ask the right questions, to develop a methodology and to merge all these data sources into a common framework for the assessment of future traffic safety innovations.
Unfallgeschehen zwischen rechtsabbiegenden Güterkraftfahrzeugen und geradeausfahrenden Radfahrern
(2014)
Abbiege-Unfälle von Fahrzeugen, bei denen Radfahrer zu Schaden kommen, gehören zu den schweren Radfahrunfällen, insbesondere, wenn sie sich in einer "Tote Winkel"-Situation mit einem Güterkraftfahrzeug ereignen. Unklar ist die genaue Anzahl der Unfälle und die Unfallschwere, welche mit dieser Unfallkonstellation in Zusammenhang stehen können. In der Unfall-Analyse wurden dazu Daten der amtlichen Straßenverkehrsunfallstatistik der Jahre 2008 bis 2012 untersucht. Festgestellt wurde, dass diese Unfälle lediglich 1 % aller Radfahrunfälle sowie rund 6 % der insgesamt 406 getöteten Radfahrer darstellen. Durch eine weitere Differenzierung von "Tote Winkel"-Unfällen nach dem zulässigen Gesamtgewicht der Güterkraftfahrzeuge konnte festgestellt werden, dass die schweren Unfälle überwiegend geprägt sind von schweren Güterkraftfahrzeugen mit zulässigem Gesamtgewicht über 7,5 t sowie Sattelschleppern. Theoretisch wird bei jedem 10. "Tote Winkel"-Unfall zwischen einem rechtsabbiegenden, schwerem Güterkraftfahrzeug und einem geradeausfahrenden Radfahrer ungefähr ein Radfahrer getötet. Im laufenden Forschungsvorhaben "Toter Winkel " Konflikt zwischen rechtsabbiegenden Lkw und geradeausfahrendem Radverkehr" sollen die Verkehrssicherheitsdefizite analysiert werden. Des Weiteren wurde ein Forschungsvorhaben "Entwicklung eines Testverfahrens für Nutzfahrzeug-Abbiegeassistenzsysteme" initiiert, um eine Testkonfiguration für die Detektion von Radfahrern und die Warnung des Fahrzeugführers auf Basis von Unfallszenarien abzuleiten.
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.
Analysis of the accident scenario of powered two-wheelers on the basis of real-world accidents
(2013)
For the first time since 20 years the German national statistics of traffic accidents revealed an increasing number of fatalities and seriously injured persons in 2011. This negative development was especially caused by increasing numbers in all groups of vulnerable road users (VRU). Furthermore, the comparison of fatality reduction rates between several categories of road users shows that persons on motorcycles show the worst performance over years. Although every second fatality in German traffic accidents is still a car occupant, users of PTW make up more than 20% in the meantime. Assuming further improvements in the field of occupant protection this trend will continue. For that reason, a study on the basis of real-world accidents was conducted to describe the accident scenario involving motorcycles and to identify the reasons of the above-described fact. Approximately 1.800 motorcycle accidents out of GIDAS database were used for the analyses. The first part of the study deals with the question how representative the GIDAS database is for the German motorcycle accident scenario. Afterwards, detailed descriptive statistics on motorcycle accidents were presented considering numerous parameters about the accident scene, environmental influences, vehicle information, individual characteristics, interview data, injury severity and injury causation. One important point is the identification of the most frequent critical situations that are typical for motorcycle accidents. Furthermore, a special focus was on accident causation. Finally, conspicuous facts out of the analysis are emphasized. All in all, the study gives a comprehensive overview about the German motorcycle accident scenario. One the one hand, the use of weighted GIDAS data allows representative and robust statements on the basis of large case numbers; on the other hand highly detailed conclusions can be drawn. The results of the study help to understand the particularities of motorcycle accidents and provide approaches for further improvements in the field of PTW safety.
With an ever rising human life expectancy the share of elderly people in society is constantly rising. This leads to the fact that at the same rate the share of people with age related diseases such as dementia and poor eyesight taking part in traffic will rise and therefore traffic accidents caused by this group of people due to the disease will play an ever greater role. This Situation will be among the future challenges of road safety work. At present this study displays specific characteristics of accidents caused by elderly car drivers (aged 65 or higher) based on the analysis of the German In-Depth Accident Study GIDAS. Herein almost 1000 elderly car drivers were identified as accident participants in the years 2008 to 2011. The focus of this study lies on identifying special types of accidents which are caused by elderly drivers and on characterizing these types with the information gathered on scene and by interviewing the participants. The main evidence analyzed is the knowledge about the accident locality, the trajectories of the participants as well as the reasons for the occurrence of the accidents. Furthermore personal information such as the personal condition before the accident and driving purposes is used to identify patterns of contributing circumstances for accidents caused by elderly traffic participants.
The number of road accidents in Portugal has decreased significantly in the last decades, however, this tendency is not similar in all types of transportation. In the most recent years and by European standards, Portugal is still one of the leading countries concerning the number of fatalities in Powered Two Wheelers (PTW) accidents. To this effect, the in-depth investigation of PTW accidents is crucial and so, a thorough statistical analysis concerning the main factors influencing PTW riders injury severity accidents was undertaken regarding the 2007-2010 period in the National Road Safety Authority (ANSR) injured riders database using the software SPSS. In addition, to determine the importance of absent factors in the database analysis, such as velocity, a set of 53 real accidents involving PTW were also investigated and computationally reconstructed using the software PC-Crash. Lateral collisions between a motorcycle, its rider and the side of three different passenger cars were also simulated, varying the motorcycle impact angle and velocity in order to estimate the PTW deformation energy and the rider- injuries, as this accident configuration stands out in terms of frequency and even severity. The results of this detailed study are presented.
Abschätzung der Gesamtzahl Schwerstverletzter in Folge von Straßenverkehrsunfällen in Deutschland
(2010)
Die Zahlen der im Straßenverkehr Getöteten, Schwer- und Leichtverletzten werden in Deutschland seit Jahren in amtlichen Statistiken geführt. Über die Gruppe der besonders schwer betroffenen Patienten liegen jedoch nur vage Schätzungen vor. Auch werden unterschiedliche Kriterien zur Definition dieser so genannten Schwerstverletzten verwendet, die zumeist auf einer Beschreibung der Art und der Schwere der Verletzungen beruhen. In der vorliegenden Arbeit sollen mit Daten aus dem Trauma-Register der DGU sowohl die unterschiedlichen Definitionen dargestellt werden, als auch über verschiedene Methoden die Gesamtzahl dieser Personen in Deutschland geschätzt werden. Das TraumaRegister DGU (TR-DGU) ist eine freiwillige Dokumentation von Unfallopfern, die lebend eine Klinik erreichen, dort behandelt werden und intensivmedizinisch betreut werden müssen. Das Register besteht seit 1993 und erfasst derzeit etwa 6.000 Fälle pro Jahr aus über 100 Kliniken. Pro Patient werden ca. 100 Angaben einschließlich der Codierung seiner Verletzungen gemäß Abbreviated Injury Scale (AIS) erfasst. Dieser Codierung erlaubt die Berechnung des Injury Severity Score (ISS) und des New ISS (NISS). Zum Vergleich werden folgende Definitionen eines Schwerstverletzten betrachtet: Maximum AIS ≥ 3; Maximum AIS ≥ 4; ISS ≥ 9; ISS ≥ 16; NISS ≥ 16, Polytrauma sowie die Notwendigkeit der Intensivtherapie. Am Beispiel des Kriteriums "ISS ≥ 16" werden schließlich auf drei verschiedene Arten die Gesamtzahl Schwerstverletzter Verkehrsunfallopfer geschätzt: 1.) in fünf ausgewählten Regionen werden die Schwerstverletzten aus dem TR-DGU mit der Anzahl Schwerverletzter aus der amtlichen Statistik verglichen, um den Anteil der besonders schwer betroffenen Patienten zu bestimmen. 2.) Aus dem TR-DGU wird je nach Versorgungsstufe des Krankenhauses (lokales, regionales oder überregionales Zentrum) die durchschnittliche Anzahl Schwerstverletzter ermittelt und dann über die Anzahl solcher Kliniken in Deutschland hochgerechnet. 3.) Die Zahl der Schwerstverletzten wird aus der Zahl der Getöteten Verkehrsunfallopfer geschätzt. Dazu nutzt man das Verhältnis von in der Klinik verstorbenen zu überlebenden Schwerstverletzten aus dem TR-DGU. Mit Literaturangaben zum Anteil von präklinisch Verstorbenen wird dann auf der Basis der Anzahl der Getöteten aus der amtlichen Statistik die Gesamtzahl Schwerstverletzter geschätzt. Je nach Definition eines Schwerstverletzten konnten zwischen 9.213 und 17.425 Fälle aus dem TR-DGU der letzten 10 Jahre berücksichtigt werden. Von diesen Patienten sind zwischen 12,7% und 20,2% im Krankenhaus verstorben. Die Krankenhaus Liegedauer der Überlebenden liegt zwischen 30 und 35 Tagen. Nimmt man die Definition "ISS -³ 16" als Basis (n=13.467), so reduziert sich die Zahl Schwerstverletzter um 37%, wenn man stattdessen den Begriff des Polytraumas wählt; betrachtet man hingegen die Intensivpflichtigkeit als Kriterium so erhöht sich die Zahl um 22%. Der erste Schätzansatz kommt zum Ergebnis, dass etwa 8-10% der Schwerverletzten zu den besonders schwer Verletzten zählen. Für ganz Deutschland erhält man damit Schätzwerte zwischen 6.300 und 7.900 Fälle pro Jahr. Die zweite Methode ergab, dass die Krankenhäuser der drei unterschiedlichen Versorgungsstufen jeweils 30,2, 11,5 oder 3,3 Fälle pro Jahr behandeln. Bezogen auf die 874 deutschen Kliniken ergeben sich geschätzte Gesamtzahlen von 6.800 bis 10.400 Fälle. Die dritte Methode zeigt, dass pro Patient, der im Krankenhaus verstirbt, 6,3 Schwerstverletzte überleben. Im Krankenhaus versterben jedoch etwa nur 25% bis 40% der insgesamt Getöteten; der Großteil der Getöteten verstirbt unmittelbar an der Unfallstelle. Damit müssen noch 1,5 bis 3 Todesfälle hinzugerechnet werden, was schließlich zu einem Verhältnis von 6,3 Schwerstverletzten zu 2,5 bis 4 Todesfällen führt. Bei einer Gesamtzahl von 5.595 Getöteten (Mittelwert 2002-2008) ergeben sich so Gesamtzahlen von 8.800 bis 14.000 Schwerstverletzte pro Jahr. Die Ergebnisse der angewendeten Schätzmethoden variieren stark und lassen auf eine Gesamtzahl von etwa 10.000 schwerstverletzten Verkehrsunfallopfern pro Jahr in Deutschland schließen. Bei Anwendung der Definition Intensivtherapie ergeben sich sogar etwa 12.500 Fälle. Alle Schätzmethoden sind gewissen Unsicherheiten ausgesetzt, die wenn möglich in Variationsrechnungen berücksichtigt wurden. Eine deutlich verbesserte Schätzung dieser Zahl ist jedoch erst möglich, wenn in wenigen Jahren vollzählige Erfassungen aus den derzeit entstehenden regionalen TraumaNetzwerken der DGU im TraumaRegister vorliegen.
Estimation of the benefits for the UK for potential options to modify UNECE Regulation No. 95
(2010)
The side impact problem in Europe remains substantial. UK data shows that between 22% and 26% of car occupant casualties are involved in a side impact, but this rises to between 29% and 38% for those who are fatally injured. This indicates the more injurious nature of side impacts compared with frontal impacts. The European Enhanced Vehicle safety Committee (EEVC) has performed work to address the side impact issue since 1979. As part of its continuing work, it has recently investigated potential options for regulatory changes to improve side impact protection in cars further. To support this work the UK undertook an analysis to estimate the benefit for potential options to modify UNECE Regulation 95. The analysis used the UK national STATS19 and detailed Co-operative Crash Injury Study (CCIS) accident databases. Of the potential options reviewed, it was found that the addition of a pole test offered the greatest benefit.
The overall purpose of the ASSESS project is to develop a relevant and standardised set of test and assessment methods and associated tools for integrated vehicle safety systems, primarily focussing on currently available pre-crash sensing systems. The first stage of the project was to define casualty relevant accident scenarios so that the test scenarios will be developed based on accident scenarios which currently result in the greatest injury outcome, measured by a combination of casualty severity and casualty frequency. The first analysis stage was completed using data from a range of accident databases, including those which were nationally representative (STATS19, UK and STRADA, SE) and in-depth sources which provided more detailed parameters to characterise the accident scenarios (GIDAS, DE and OTS, UK). A common analysis method was developed in order to compare the data from these different sources, and while the data sets were not completely compatible, the majority of the data was aligned in such a way that allowed a useful comparison to be made. As the ASSESS project focuses on pre-crash sensing systems fitted to passenger cars, the data selected for the analysis was "injury accidents which involved at least one passenger car". The accident data analysis yielded the following ranked list of most relevant accident scenarios: Rank Accident scenario 1 Driving accident - single vehicle loss of control 2 Accidents in longitudinal traffic (same and opposite directions) 3 Accidents with turning vehicle(s) or crossing paths in junctions 4 Accidents involving pedestrians The ranked list highlights the relatively large role played by "accidents in longitudinal traffic", and "accidents with turning vehicle(s) or crossing paths in junctions" (the second and third most prevalent accident scenarios, respectively). The pre-crash systems addressed in ASSESS propose to yield beneficial safety outcomes with specific regard to these accident scenarios. This indicates that the ASSESS project is highly relevant to the current casualty crash problem. In the second stage of the analysis a selection of these accident scenarios were analysed further to define the accident parameters at a more detailed level .This paper describes the analysis approach and results from the first analysis stage.
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.
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.
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.
One of the major problems of road safety in Europe is the powered two wheelers accidents. One of the European countries with one of the highest rates is Portugal where in 2006, mopeds and motorcycles fatalities represented 27% of all road users deaths. In this work, a deep analysis and overview of the current state of mopeds and motorcycles accidents for the 2004-2006 period is presented. Within this period 830 PTW occupants die, 2958 have been severely injured and 25000 suffer slight injuries. A detailed analysis of the conditions of these accidents has been carried out, using the data of the national accident database. This analysis provides global information, about geographic environmental conditions, driver- characteristics among others. From this data detailed information is obtained allowing to know when, where and who. In order to answer the question why more a widely collection of data has been collect for 70 accidents. The data has been collected using OECD methodology. For these accidents a detailed reconstruction has been carried out, what is especially important for fatal accidents where for instance speed in an important factor. From these collection and analysis of data a wider overview of facts and measures are extracted. Among them, some are emphasized such as that the quality and non-use of helmets plays an important role in severe and fatal accidents especially for accidents involving moped vehicles, or speed is the most important factor in fatal accidents involving motorcycles. Concerning motorcycle accident reconstruction, different tools can be used depending of the accident scenario and complexity. For simple cases, with specific characteristics, analytical formulation based in vehicle crash dynamics can be use in order to determine the impact speed of the vehicles impact, analysing the skid marks, deformations, victims rest position and considering parameters (EES, vehicle deceleration, etc). Aspects such as the energy absorption capability of motorcycles are also discussed. In the general cases the accident reconstruction software Pc-Crash has been used for the reconstruction of the accident. In very complex cases, has for instance the impact between motorcyclist and barriers, Madymo software is used especially to determine speed from injuries. An example of the impact of a motorcyclist and a motorcyclist-friendly barrier is present to illustrate the benefits and limitations of such systems.
Novice drivers are at high risk for crash involvement. We performed an analysis of causations, injury patterns and distributions of novice drivers in cars and on motorcycles in road traffic as a basis for proper measurements. Method Data of accident and hospital records of novice drivers (licence < 2 years) were analysed focusing the following parameters: injury type, localisation and mechanism, Abbreviated Injury Scale (AIS), maximum AIS (MAIS), delta-v, collision speed and other technical parameters and have been compared to those of experienced drivers. In 18352 accidents in the area of Hannover (years1985"2004), 2602 novice drivers and 18214 experienced drivers were recorded having an accident. Novice car drivers were more often and severe injured than experienced and on motorcycles the experienced riders were at higher risk. Novice drivers of both groups sustained more often extremity injuries. 4.5 % novice car drivers were not restraint compared to 3.7 % of the experienced drivers and 6.1 % novice motorcycle drivers did not wear a proper helmet (versus 6.5 %). Severe injuries sustained at a rate of 20 % at collision speeds below 30 km/h and in 80% at collision speeds above 50 km/h. Novice car drivers drove significant older cars. The risk profile of novice drivers is similar to those of drivers older than 65 years. Structural protection and special lectures like skidding courses could be proper remedial action next to harder punishment of violations.
Side impacts, both nearside and farside, have been indicated by research to be responsible for a large proportion of serious injuries from road crashes. This study aimed to compare and contrast the characteristics of nearside and farside crashes in Australia, Germany and the U.S., using the ANCIS, GIDAS and NASS/CDS in-depth-databases, in order to establish the impact and injury severity associated with these crashes, and the types of injuries sustained. The analyses revealed some interesting similarities, as well as differences, between both nearside and farside crashes, and the emergent trends between the three investigated countries. More specifically, it was indicated that whilst the severity of injury sustained in nearside crashes was slightly greater overall than that found for farside crashes, careful consideration of struck and nonstruck side occupants must be made when considering aspects such as vehicle design and occupant protection.
Untersuchungsgegenstand des Forschungsprojektes war die Überprüfung der aktuellen Grenzwertkriterien in Deutschland zur Identifizierung von Unfallhäufungen im Straßennetz. Nach Analyse des IST-Zustandes und der Bestimmung von Defiziten wurden alternative Grenzwertkriterien mit dem Ziel eines optimierten Einsatzes von Ressourcen im Bereich der Örtlichen Unfalluntersuchung überprüft. Auf Grundlage dieser Erkenntnisse erfolgte die Ableitung von Empfehlungen für zukünftige Grenzwertkriterien. Insgesamt wurden verschiedene Grenzwertkriterien getrennt für die Ortslagen innerorts, außerorts (ohne BAB) und Bundesautobahnen mittels einer umfangreichen Unfalldatenauswertung untersucht. Als Untersuchungsgebiete dienten außerorts Bereiche von Bundesländern (Sachsen) oder ganze Bundesländer (Bayern, Rheinland-Pfalz) sowie innerorts Städte verschiedener Größe (Großstädte über 100.000 E, Mittelstädte mit 30.000 bis 100.000 E sowie Durchfahrten von Ortschaften unter 30.000 E) aus vier Bundesländern. Die Untersuchungen lassen sich in folgenden Ergebnissen zusammenfassen:- Bei der Bestimmung der unfallauffälligen Stellen (UAS) mit gleichartigen Unfällen werden ortslagenunabhängig nahezu alle UAS durch die Gleichartigkeit des Unfalltyps identifiziert. Durch die Berücksichtigung von Unfallumständen wie z.B. die Verkehrsbeteiligung werden kaum zusätzliche Stellen erkannt. - Bei der parallelen Betrachtung der drei aktuellen Auswertungszeiträume (1-Jahreskarte, 3-Jahreskarte (P) und 3-Jahreskarte (SP)) wurde festgestellt, dass ein Großteil der UAS, die in der 3-Jahreskarte (SP) auffällig sind, auch in der 3-Jahreskarte (P) als auffällig identifiziert werden. - Die zeitliche Stabilität, d.h. das wiederholte Auftreten eines unfallauffälligen Bereiches in zwei oder mehr aufeinanderfolgenden Betrachtungszeiträumen, erreicht gemessen am Anteil an allen unfallauffälligen Bereichen in einem Ausgangszeitraum weder bei den UAS noch bei den unfallauffälligen Linien (UAL) eine zufriedenstellende Größenordnung. - Aus den unterschiedlichen Kriterien für die Optimierung von Grenzwerten nach einem ausgewogenen Verhältnis von Aufwand und Nutzen resultieren zum Teil unterschiedliche Ergebnisse. Bei der Empfehlung neuer Grenzwerte wurde darauf geachtet, dass bei Anwendung des Grenzwertes mindestens 10% des Gesamtunfallgeschehens im jeweiligen Betrachtungszeitraum bearbeitet werden. Die Empfehlungen beinhalten für die Identifizierung von unauffälligen Bereichen insbesondere Vorschläge zu geeigneten Betrachtungszeiträumen, räumlichen Abgrenzungen von unfallauffälligen Bereichen sowie der Angabe optimierter Grenzwerte differenziert nach Ortslage und Betrachtungszeitraum.
Empirical vehicle crashworthiness studies are usually based on national or in-depth traffic accident surveys: Data on accident-involved cars/drivers are analysed in order to quantify the chance of driver injury and to assess certain risk factors like car make and model. As the cars/drivers involved in the same accident form a "cluster", where the size of the cluster equals the number of accident-involved parties, traffic accident survey data are typical multi-level data with accidents as first-level or primary and cars/drivers as secondlevel or secondary units (car occupants in general are to be considered as third level units). Consequently, appropriate statistical multi-level models are to be used for driver injury risk estimation purposes as these models properly account for the cluster structure of traffic accident survey data. In recent years various types of regression models for clustered data have been developed in the statistical sciences. This paper presents multi-level statistical models, which are generally applicable for vehicle crashworthiness assessment in the sense that data on single and multiple car crashes can be analysed simultaneously. As a special case of multi-level modelling driver injury risk estimation based on paired-by-collision car/driver data is considered. It is demonstrated that assessment results may be seriously biased, if the cluster structure inherent in traffic accident survey data is erroneously ignored in the data analysis stage.
In the context of this study, different data sources for accident research were examined regarding their possible data access and evaluated concerning the individual quality and extent of the data. Analyses of accidents require detailed and comprehensive information in particular concerning vehicle damages, injury patterns and descriptions of the accident sequence. The police documentation supplies the basic accident statistics and is amended in the context of the forensic treatment by further information, e.g. by medical and technical appraisals and witness questionings. As a new approach to the data acquisition for the analysis of fatal traffic accidents, the information was made usable which was collected by the police and by the investigations of the public prosecutor. The best strategy for obtaining reliable, extensive and complete data consists of combining the information from these two sources: the very complete, but elementary statistic data of the Niedersächsisches Landesamt für Statistik (Lower Saxony State Authority of Statistics), based on the police documentation as well as the very extensive accident information resulting from the investigation documentation of the public prosecutor after conclusion of the procedure, the so-called Court Records. Of all 715 fatal traffic accidents, which happened in the year 2003 in the German State of Lower Saxony, 238 cases were selected by means of a statistically coincidental selective procedure based on a statistically representative manner (every third accident). These cases cover the investigation documents of the 11 responsible public prosecutor- offices, which were requested and evaluated while preserving the data security. Of the 238 cases 202 cases were available, which were individually coded and stored in a data base using 160 variables. Thus a data base of a sample of representative data for fatal accidents in Lower Saxony was set up. The data base contains extensive information concerning general accident data (35 variables), concerning road and road surface data (30 variables), concerning vehicle-specific data (68 variables) as well as concerning personal and injury data (27 variables).
In recent years special attention has been paid to reducing the number of fatalities resulting from road traffic accidents. The ambitious target to cut in half the number of road users who are killed each year by 2010 compared with the 2001 figures, as set out in the European White Paper "European Transport Policy for 2010: Time to Decide" implies a general approach covering all kinds of road users. Much has been achieved, e.g. in relation to the safety of car passengers and pedestrians but PTW accidents still represent a significant proportion of fatal road accidents. More than 6,000 motorcyclists die annually on European roads which amounts to 16% of the EU-15 road fatalities. The European Commission therefore launched in 2004 a Sub- Project dealing with motorcycle accidents within an Integrated Project called APROSYS (Advanced PROtection SYStems) forming part of the 6th Framework Programme. In a first step, the combined national statistical data collections of Germany, Italy, the Netherlands and Spain were analysed. Amongst other things parameters like accident location, road conditions, road alignment and injury severity have been explored. The main focus of the analysis was on serious and fatal motorcycle accidents and the results showed similar trends in all four countries. From these results 7 accident scenarios were selected for further investigation via such in-depth databases as the DEKRA database, the GIDAS 2002 database, the COST 327 database and the Dutch element of the MAIDS database. Three tasks, namely the study of PTW collisions with passenger cars, PTW accidents involving road infrastructure features, and motorcyclist protective devices have been assessed and these will concentrate inter alia on accident causes, rider kinematics and injury patterns. A detailed literature review together with the findings of the in-depths database analysis is presented in the paper. Conclusions are drawn and the further stages of the project are highlighted.
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.