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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).
Die Qualität der Beeinflussung und der Information des Verkehrsteilnehmers ist in hohem Maße abhängig von der Qualität der erhobenen Verkehrsdaten. Aus diesem Grunde stellt sich die Frage: welche Qualitätsanforderungen sind an die Verkehrsdatenerfassung zu stellen und wie wird sichergestellt, dass die Qualitätsanforderungen auch im laufenden Betrieb über Jahre hinweg eingehalten werden? In einem Arbeitskreis der FGSV wurden Hinweise zur Qualitätsanforderung und Qualitätssicherung der lokalen Verkehrsdatenerfassung für Verkehrsbeeinflussungsanlagen entwickelt. Das hier vorgestellte Hinweispapier, das von der FGSV veröffentlicht wurde, soll die Betreiber von Verkehrsbeeinflussungsanlagen dabei unterstützen, die Qualitätsanforderung an die lokale Verkehrsdatenerfassung zu erfüllen und im laufenden Betrieb dauerhaft sicherzustellen.
In Finland all fatal motor vehicle accidents are studied in-depth on-the-spot by multidisciplinary (police, road and vehicle engineers, physician and behavioural scientist) road accident investigation teams (legislation 2001, work started 1968), which operate in every province. The purpose of the teams is to uncover risk factors that turned an ordinary driving situation into a serious accident and give safety recommendations for improving road safety. The investigation teams do not take a stand on guilt or insurance compensation. When analysing accidents the teams use the concepts of key event, immediate, background and injury risk factors. Compiled investigation folders of each case contain investigation forms from each member, preinvestigation protocol, photographs, sketches etc. About 500 items of information are collected from each accident party. The collected information is also coded into a computer database. Both the database and the investigation folders are widely utilized by researchers and authorities conducting safety work.
Annually within the European Union, there are over 50,000 road accident fatalities and 2 million other casualties, of which the majority are either the occupants of cars or other road users in collision with a car. The European Commission now has competency for vehicle-based injury countermeasures through the Whole Vehicle Type Approval system. As a result, the Commission has recognised that casualty reduction strategies must be based on a full understanding of the real-world need under European conditions and that the effectiveness of vehicle countermeasures must be properly evaluated. The PENDANT study commenced in January 2003 in order to explore the possibility of developing a co-ordinated set of targeted, in-depth crash data resources to support European Union vehicle and road safety policy. Three main work activity areas (Work Packages) commenced to provide these resources. This paper describes some of the outcomes of Work Package 2 (WP2, In-depth Crash Investigations and Data Analysis). In WP2, some 1,100 investigations of crashes involving injured car occupants were conducted in eight EU countries to a common protocol based on that developed in the STAIRS programme. This paper describes the purposes, methodology and results of WP2. It is expected that the results will be used as a co-ordinated system to inform European vehicle safety policy in a systematic, integrated manner. Furthermore, the results of the data analyses will be exploited further to provide new directions to develop injury countermeasures and regulations.
76 severe traffic accidents had been investigated in depth in an ongoing Volkswagen-Tongji University joint accident research project in JiaDing district, Shanghai, PR China since June 2005. With a methodology similar to German accident research units in Dresden and Hannover, a research team proceeds to the scene immediately after the incident to investigate and collect various data on environment, accident occurrence, vehicle state and deformations as well as injuries. The data combined with the results of accident reconstruction will be stored in a database for further statistical and casuistic analysis. The first outcome of the project supports the hypothesis that a main causation for the large number of traffic accidents in China is the lacking of risk awareness in Chinese driver behaviour. Low seat-belt use and the high proportion of vulnerable and poorly protected two-wheelers in traffic are reasons for the high injury and fatality rate in China. The research work shows that accident research in China is feasible and able to give support to tackle one of the urging problems in Chinese development.
Internationally, the need is expressed for harmonized traffic accident data collection (PSN, PENDANT, etc.). Together with this effort of harmonization, traffic accident investigation moves more and more in the direction of accident causation. As current methods only partly address these needs, a new method was set up. The main characteristics of this method are: • Accident/injury causation (associated) factors can objectively be identified and quantified, by comparison with exposure information from a normal population. • All relevant accident and exposure data can be included: human-, vehicle-, and environmental related data for the pre-crash, crash and postcrash situation (the so-called Haddon matrix). The level of detail can be chosen depending on interest and/or budget, which makes the method very flexible. In this paper the accident collection and control group method are presented, including some of the achieved results from a pilot study on 30 truck accidents and 30 control locations. The data were analyzed by using cross-tabulations and classification-tree analysis. The method proved useful for the identification of statistically significant causational aspects.
The "Seven Steps Method" is an analysis and classification system, which describes the human participation factors and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. By means of the "seven steps" it is possible to describe the relevant human causes of accidents from persons involved in the accident in an economic way with a sufficient degree of exactitude, because the causes can be further differentiated in their value (e.g. diversion as external diversion with regard to impact due to surroundings) and their sub values (e.g. external diversion with regard to impact due to surroundings in the shape of a "capture" of the perception by a prominent object of the traffic environment). Theoretically it is possible that one or more causing moments can be assigned to a person involved in an accident in each of the "seven steps"; however it is also possible to sufficiently clarify the cause in only one level (examples for this are described). In the practice of accident investigation at the site of the accident, the sequence chart is also relevant. With its assistance the questioning of the people involved in an accident can be accomplished in a structured way by assigning a set of questions to each step.
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.