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Im Jahr 2004 fand an der Medizinischen Hochschule Hannover die erste ESAR-Konferenz (Expert Symposium on Accident Research) statt. Die Idee einer internationalen Konferenz war aus der Notwendigkeit entstanden, diejenigen Experten zusammen zu bringen, die weltweit tätig sind und Verkehrsunfälle wissenschaftlich analysieren, um ihre Ergebnisse gemeinsam zu diskutieren und einem Zielpublikum von Behördenvertretern, Entwicklungsingenieuren der Automobilindustrie und anderen Wissenschaftlern darzubringen. Die durch Professor Otte initiierte und nun zum vierten Male organisierte Konferenz fand eine breite Akzeptanz und ist mittlerweile Bestandteil einer Konferenzlandschaft mit Zielvorträgen von der Fahrzeugsicherheit bis hin zur Verletzungsanalyse und den Unfallursachen. ESAR kann als wissenschaftliches Kolloquium und Plattform für einen Informationsaustausch der Unfallforscher angesehen werden, die sich speziell mit Methoden der Unfalluntersuchung, mit Verletzungsmechanismen und der Bewertung von Verletzungen, Unfallursachen und anderen Bereichen der statistischen Unfalldatenanalyse befassen. Experten aus den Bereichen der Medizin, der Verkehrspsychologie und der Technik sowie Vertreter zuständiger Behörden kommen hier zusammen, um die Erfahrungen in der Unfallprävention und der Unfallrekonstruktion zu diskutieren und um der Forschung neue Felder zu eröffnen. Neben den Belangen der Europäischen Gemeinschaft werden auch die weltweit zu registrierenden hohen Verletztenzahlen berücksichtigt. Wissenschaftliche Vorträge aus aller Welt tragen dazu bei, geeignete Maßnahmen und Methoden zur Analyse und drastischen Verringerung der Zahl der bei Verkehrsunfällen Getöteten zu entwickeln. Die Zusammensetzung des Teilnehmerkreises dieser wie früherer ESAR-Konferenzen hat längst eine über Europa hinausgreifende Internationalitaet erreicht und bietet daher einen aufschlussreichen Überblick über die verschiedenen Standards bestehender Verkehrssicherheit und unterschiedlichen Unfallszenarien und über die Anforderungen an die Unfallanalysen. Die Ergebnisse langjähriger Forschungsarbeiten in Europa, USA, Australien und asiatischen Ländern beinhalten unterschiedliche infrastrukturelle Zusammenhänge und geben Erkenntnisse über Population, Fahrzeugbestand und Fahrereigenschaften. Derartige Informationen bilden eine exzellente Basis für abzuleitende Empfehlungen und Maßnahmen für die Erhöhung der Verkehrssicherheit international.
In 2012 the fifth ESAR conference (Expert Symposium on Accident Research) was held in Hannover. ESAR is an international convention of experts, who analyze traffic accidents all over the world and discuss their results in this context, conducted at the Medizinische Hochschule Hannover every 2 years. It connected representatives of public authorities, engineers in automotive development and scientists and offers a forum with particular emphasis on In-Depth-Analyses of accident statistics and accident analyses. Special focus is placed on research on the basis of so-called "In-Depth-Accident-Investigations" [data collections at the sites of the accidents], which are characterized by extensive documentations of the sites of the accidents, of the vehicles as well as of the injuries, encompassing several scientific fields. ESAR aims at a multi-disciplinary compilation of scientific results and at discussing them on an international, scientific level. It is thus a scientific colloquium and a platform for exchanging information for all accident researchers. Experiences in accident prevention as well as in the complex field of accident reconstruction are stated and new research fields are added. Existing results of long-term research work in Europe, the US, Australia and Japan include different infrastructural correlations and give findings on population, vehicle population and driver characteristics, which offer a basis for recommendations to be derived and measures for increasing road safety.
Road safety is a major preoccupation of the European Commission and the road transport industry and depends on numerous significant factors. In order to improve road safety and to plan effective safety improvement actions for truck transport, we must first identify the problems to be addressed, i.e. what are the main causes of truck accidents. The ETAC project, initiated by the European Commission and the IRU, was launched in order to set up a heavy goods vehicle accident causation study across European countries to identify future actions which could contribute to the improvement of road safety. The results will be based on a detailed analysis of truck accident data collected in seven European countries according to a common methodology which has been elaborated through numerous national and European projects. This paper describes the common methodology used to collect the information on the scene of the accident and to analyse the data so that the reconstruction of the crash events may be carried out. CEESAR proposes a methodology using its experience gained from over 10 years of accident data collection. This methodology is based on an in-depth investigation of the parameters involved in-an accident and linked to the driver, the vehicle, the road and their environment. In-depth investigation requires accident investigator presence on the scene of the accident in order to collect volatile information such as marks on the road, weather conditions, visibility, state and equipment of the vehicle, driver interview. Later, passive and active information is gathered, either at the hospital for the driver, at the garage for the vehicle or on the spot for the road geometry. A reconstruction carried out with the help of specific software and the analysis of the data collected and calculated enables the identification of the main causes of the accident and the future actions to plan in order to improve road safety as regards truck traffic.
Road accidents are typically analyzed to address influences of human, vehicle, and environmental (primarily infrastructure) factors. A new methodology, based on a "Venn diagram" analysis, gives a broader perspective on the probable factors, and combinations of factors, contributing both to the occurrence of a crash and to sustaining injuries in that crash. The methodology was applied to 214 accidents on the Mumbai-Pune expressway. Factors contributing to accidents and injuries were addressed. The major human factors influencing accidents on this roadway were speeding (30%) and falling asleep (29%), while injuries were primarily due to lack of seat belt use (46%). The leading infrastructure factor for injuries was impact with a roadside manmade structure (28%), and the main vehicle factor for injuries was passenger compartment intrusion (73%). This methodology can help identify effective vehicle and infrastructure-related solutions for preventing accidents and mitigating injuries in India.
For the avoidance of traffic accidents by means of advanced driver assistance systems the knowledge of failures and deficiencies a few seconds before the crash is of increasing importance. This information e.g. is collected in the German accident survey GIDAS by an interview derived from the ACAS methodology. However to display the whole range of accident causation factors additional information is needed on enduring factors of the system components "human", "infrastructure" and "machine". On the strategic level these accident moderating factors include long term influences such as medical preconditions or a general higher risk taking behavior as well as influences on the immediate conflict level such as an aggressive response to a perceived previous traffic conflict. This study was conducted to examine the feasibility of collecting such causation information in the scope of an in-depth accident investigation like GIDAS. Due to the comprehensive amount of information necessary to estimate the moderating factors the collection of the information is distributed to different methods. 5 cases of real world crashes have been investigated where information was collected on-scene and retrospective by interviews. The identified moderating factors of the accidents and the method for collecting the information are displayed.
It is very important for Automotive OEMs to get feedback on their product performance on real roads for continuous improvement. Every OEM has a way of collecting this feedback for various performance parameters. Systematic accident research is a way to generate the information related to safety performance of the vehicle. In India, while there is a large amount of data related to the accidents, it is found this data is aimed at understanding the gross statistics and not directly useful for technology development. This paper explains learnings from a pilot study carried out in collaboration with an Emergency Medical Services provider on one of the expressways (motorways). This pilot study has resulted in development of working model that could now be scaled up at for wider application. The paper also presents some of the important observations based on the data collected.
While accident statistics on a national level are provided by many countries, there is a need for international data that includes more detailed information about the accident, so called in-depth data. As a consequence, accident data projects have been emerging in different regions of the world. This creates a need for comparable and mergeable data from different countries, enabling the use of already existing accident data resources and helping to expedite the improvement of global road safety. While existing approaches focus that mostly on building a comprehensive accident database from scratch, the iGLAD project (Initiative for the Global Harmonization of Accident Data) attempts a more pragmatic approach by building on top of the work already accomplished in this area and complementing it. The target of iGLAD is to help setting up an additional dataset as a compatibility layer between already existing world wide data sets and integrating the structure of these by defining a common data scheme. This dataset is limited to the common denominator between the existing data sets and is inherently rather small and simple. Eventually, an individual converter for each participating accident investigation group will be built that enables pooling all data sets in a common repository. This not only saves costs and time, and hence makes such a target more feasible, but also creates data that is usable right from the start. This paper gives an overview of the current status of iGLAD and first steps taken. Additionally, some methodological aspects are discussed, next to a glance at other projects working currently on related issues, providing additional input for iGLAD. Finally, an overview of next steps and intended future work is given.
Accidents with vulnerable road users require special attention within the road safety work because these accidents are often accompanied with severe injuries. Thus In 2006 at least 6200 Powered Two Wheeler (PTW) riders were killed in road crashes in the EU 25 representing 16% of the total number of road deaths while accounting for only 2% of the total kilometers driven. For the prevention of accidents with VRU above all the knowledge of the causes of the accidents is of special importance. This study is based on the methodology of the German In-Depth Accident Study GIDAS. Within GIDAS extensive data on various fields of accidentology are collected on-scene from road traffic accidents with injuries in the Hannover and Dresden area. Using a well defined sample plan the collected data is highly representative to the whole German situation (Brühning et al, Otte et al). The need of in-depth accident causation data in accident research led to the development of a special tool for the collection of such data called ACASS (Accident Causation Analysis with Seven Steps), which was implemented in the GIDAS methodology in 2008 and described by Otte in 2009.
This contribution introduces a number of psychological methods of analysis that are based on the practice-oriented collection of information directly at the site of an accident and that allow for an analysis and coding of the accident causes. Investigation examples and examples of the data combinations with basic medical and technical data are outlined. Objective of the collection is the inter-disciplinary investigation of human factors in the causes of accidents ("human-factor-analysis"). The psychological data are incorporated according to an integrative model for accident causes based on empiric algorithms in the data base of the accident research, where the clustered evaluation potential of comprehensive factors of the accident development can be illustrated. The central theoretical concept for the basic model of the progress of the accident from a psychological point of view comprises psychological indicators for the evaluation of the site of the accident for the analysis of the perception conditions as well as a classification of the gleaned data into the accident progress model according to chronological and local criteria. Perception conditions, action intentions and executions as well as conditions limiting perception and actions are acquired, using a questionnaire for persons involved in an accident, and are also integrated into the data structure concerning weighted feature characteristics as well as combined with other relevant features. Suitable systematization tools for the collection and coding of psychological accident development parameters have to be provided, which require primarily a model image of the corresponding processes from the persons involved in the accident (perceptions, expectations, decisions, actions). The interactive accident model contains components of the models by KÜTING 1990, MC DONALD 1972, SURREY 1969 and RASMUSSEN 1980. Based on the inter-action of the three partial systems "person", "vehicle" and "environment", the first step is the assessment of the situation by the persons involved in the accident. This is dependent on the personal attitudes and motives, on experiences and expectations concerning the progress of the situation. Subsequently, data concerning the manner of the coping with the ambiguous state as well as with the instable state (emergency reaction immediately before the accident occurs) are collected. The factors relating to the persons involved in the accident are gathered on several levels using corresponding questionnaires. The coding of the found and collected characteristics is conducted in a multidimensional evaluation relating to the technical results of the accident reconstruction and of the psychological classification, which are subsequently integrated in coded form into the data base of the accident research. The result of this analysis is a description of the development of the accident depicted on a chronological vector from a perception and decision theoretical perspective. This is explained in detail using exemplary cases.