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The second ESAR Conference took place at the Medical University Hannover. This year conference presents the current state of affairs of relevant research activities in the field of in-depth investigations. The first conference on ESAR (Expert Symposium on Accident Research) was established in 2004. It is planned to hold ESAR every two years. Hannover seems to be the right place for this conference concerning the fact that the first in-depth research team was found here in the year 1973 and comprehensive studies on accident analysis were spread out from here around the world continuously. This year conference topped all expectations in terms of the numbers of participants, in the variety of papers and the interdisciplinary of presenters from medical, psychological and engineering background. More than 100 delegates from all over the world, that means 13 different countries and from 4 different continents, came to Hannover, presented their results of accident investigation and discussed countermeasures for accident prevention and injury reduction. ESAR should be a platform for exchange of knowledge to find an optimized way for increase of traffic and vehicle safety by in-depth investigation and methodology. ESAR as international conference should be a platform for consideration of all nations round the world. This seems to be very important for the current situation, having high safety in the high industrial countries of Europe, US and Australia, but low safety and high injury risk in Asia and Africa.
This paper uses the national accident statistics of Great Britain to evaluate the effectiveness of Electronic Stability Control Systems (ESC) to reduce crash involvement rates. The crash experience of 8,951 cars is analysed and compared to a closely matching set of non-ESC cars using case-control methods. This is one of the largest ESC samples analysed to date. Overall the cars with ESC are involved in 3% fewer crashes although the effectiveness is substantially higher under conditions of adverse road friction. ESC equipped cars are involved in 15% fewer fatal crashes although this reduction represents the combined effect of ESC and passive safety improvements.
The primary goal of this investigation was to determine the relative risk of traffic accidents in students. In a two year period, a survey amongst 2,325 students was carried out, and 3,645 injuries sustained by students treated at our hospital were analyzed. Moped-riding in adolescents were associated with a 23.75-fold increased risk for injury as compared to biking. Children who ride bicycles have a 2.2-fold increased risk for an injury sustained by traffic accidents compared to pedestrians. None of 50 injured bicycle riders with helmet had an AIS for head injuries of more than 2. 24 of 233 injured bicycle drivers without helmet had an AIS for head injuries of more than 2. The use of a protective helmet significantly reduced the severity of head injuries. The level of awareness towards danger and a history of previous accidents correlate with the likelihood of future accidents. Due to the severity of traffic accidents, more adequate prevention measures (wearing of bicycle helmets and better education for moped riders) are urgently needed.
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).
The number of injuries sustained by car occupants involving the head, thorax, spine, pelvis and the upper limbs have been reduced significantly during recent years. This is probably due to better safety features in the cars, especially the availability and usage of safety belts, airbags etc. Therefore one can notice clinically a relative increase in survivors of severe frontal crashes, but many of them have injuries to the lower extremities. To verify this, we analyzed the foot and ankle injuries of front seat passengers.
This study examines the severity and types of injuries sustained by child pedestrians aged 18 years and below in order to identify the body regions at greatest risk for injury in a pedestrian accident. Detailed medical diagnoses were reviewed retrospectively for 572 child pedestrians admitted to an urban pediatric trauma center with injuries during the time period from January 2001 to December 2005. Eighty percent of these children sustained AIS 2 or greater injuries, most commonly to the lower extremity (41%) and head (34%). Fortyfour percent of admitted children had more significant AIS 3 or greater injuries primarily to the head (58%), thorax (17%) and lower extremities (14%). Testing procedures to assess the child- interaction with the motor vehicle should include injury assessment for the pediatric head, thorax and lower extremities. This understanding of how child pedestrians interact with motor vehicles may provide insight into effective countermeasures with potential for implementation in vehicle designs world-wide.
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.
While the number of fatal accidents is diminishing every year, there is still a need of improvement and action to prevent these deaths. Basis for this purpose has to be an analysis about the factors influencing the car crash mortality. There are various studies describing the univariate influence of several factors, but crash scenarios are too complex to be described by a single variable. The multivariate analysis respects the interference of the variables and gets so to more detailed and representative results. This multivariate analysis is based on about 2,600 cases (the data have been collected by the accident research units Hannover and Dresden (during the years 1999-2003). This paper presents a multivariate model (containing ten different variables) which detects 93% of these cases properly. This means it detects the cases as truly survived and truly death.
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.
NASS: the glass is half full
(2007)
The National Accident Sampling System (NASS) was born in the late 1970s. It was based on a substantial amount of experience and analysis of what was needed in the United States to understand the safety challenges of our highways. This work also showed how to collect high quality and useful crash data efficiently. Unfortunately, when Ronald Reagan - a President who believed in limited government - was elected, any hope of full funding for NASS was lost. The concept of 75 teams investigating about 18,000 serious crashes in detail annually was never realized. The system got up to 50 teams, then was cut to 36, and finally to 24 teams investigating fewer than a quarter of the originally anticipated number of crashes per year. Despite this, the NASS investigations provide a rich source of data, collected according to a sophisticated statistical sampling system to facilitate detailed national estimates of road casualties on our nation- highways and their causes. In addition, changes have been made in recent years to increase the number of more serious crashes of recent model vehicles to make the results more relevant to improving vehicle safety. A recent, detailed examination of hundreds of rollovers has provided considerable insight into rollover casualties and into what can be done to reduce them. Some of these results will be presented that show the value of the NASS system. Our experience with NASS and the Fatal Accident Reporting System (FARS) suggests a number of improvements that could be made in the United States" crash data systems. It also provides justification for a doubling or tripling of our national expenditures on crash data collection.