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The Centre for Automotive Safety Research (formerly the Road Accident Research Unit) at the University of Adelaide in South Australia has a history of in-depth crash investigation going back to the 1970s. In recent years, our focus has been on studying factors that contribute to road crashes, with an emphasis on the role of road infrastructure. Our method involves crash notification by the South Australian Ambulance Service and detailed investigation of the crash scene usually before the crash-involved vehicles have been moved. This at-scene data collection is supplemented with police crash reports, Coroner- reports including autopsy findings for fatal crashes, case notes from hospitals for all injured persons, structured interviews with crash participants and witnesses, and computerised reconstruction of the events of the crash. One of the most notable research findings to emerge from our in-depth work has been the relationship between travelling speed and the risk of crash involvement. By comparing the calculated free speeds of crash-involved vehicles (cases) with the measured speeds of non-crash-involved vehicles travelling on the same roads at the same time of day (controls), we were able to establish that an exponential relationship exists between travelling speed and the likelihood of involvement in a casualty crash. This was the case for both metropolitan and rural areas. This research prompted the reduction of some speed limits in Australia, which has resulted in notable decreases in crash numbers. Another finding of interest in our recent investigation of 298 mostly daytime crashes in metropolitan Adelaide was that medical conditions make a sizeable contribution to the occurrence of road crashes. We found that almost half of the drivers, riders and pedestrians involved in the collisions had at least one pre-existing medical condition, and half of these individuals had two or more such conditions. We found that a medical condition was the direct causal factor in 13% of the casualty crashes investigated and accounted for 23% of all hospital admission or fatal crash outcomes. A follow-up study of all hospital admissions for road crashes in Adelaide is now going ahead to look further at this problem. The paper also describes studies looking specifically at pedestrian crashes. These include studies of the relationship between travelling speed and the risk of a fatal pedestrian crash, and studies utilising real crash data to validate headforms and test dummies used in the assessment of the safety of new vehicles in the event of a collision with a pedestrian.
The aim of this study is to investigate the differences in car occupant injury severity recorded in AIS 2005 compared to AIS 1990 and to outline the likely effects on future data analysis findings. Occupant injury data in the UK Cooperative Crash Injury Study Database (CCIS) were coded for the period February 2006 to November 2007 using both AIS 1990 and AIS 2005. Data for 1,994 occupants with over 6000 coded injuries were reviewed at the AIS and MAIS level of severities and body regions to determine changes between the two coding methodologies. Overall there was an apparent general trend for fewer injuries to be coded at the AIS 4+ severity and more injuries to be coded at the AIS 2 severity. When these injury trends were reviewed in more detail it was found that the body regions which contributed the most to these changes in severity were the head, thorax and extremities. This is one of the first studies to examine the implications for large databases when changing to an updated method for coding injuries.
Automotive Engineering, Mechanical Engineering and TechnologyrnAbstract: The degrees of injury severity, as a rule injuries scaled by AIS of specific regions of the human body, investigated out of road traffic accidents correspond to the body-specific loading values, which are found out with the aid of experimental or mathematical simulation of crash tests with motor vehicles or with sled tests. The coherence between the injured human being on the one hand and the physical and the theoretical model respectively on the other hand is established by the risk function, which describes the probability of degrees of injury severity in dependence on the protection criteria. Due to the different physical characteristics in the simulation, e.g. accelerations, forces, compressions and their velocity, the compilation of these quantities, comparable to the MAIS, the maximal occurred single AIS obtained in accident analysis is much more difficult in the simulation than in the accident occurrence. Therefore it is obvious to normalize the loading values gained out of simulation and to summarise them to an entire value in a suitable manner, the safety index.rn
The fact that ADAC Air Rescue handles approximately 4,000 road accident missions every year gave rise to set up an accident research programme for which ADAC Air Rescue provides its data. This data is of initial informational quality and will be supplemented by data from the police, experts, fire brigades as well as hospitals and forensic institutes. Although the number of cases is still rather low, certain tendencies can be identified. The causes for most accidents occur when joining or intersecting traffic, followed by speeding in road bends and tailgating. Many accidents involve HGV rear end collisions, often causing serious injuries, considerable damage and technical problems for the rescue operations. With regard to the various impact types, it has become obvious that most of the extremely serious injuries are inflicted during a passenger car side impact. In addition, access to and removal of trapped passengers is becoming more and more complicated, partly due to the increasing use of high-strength materials, and rescue operations tend to be more time consuming.
Bicyclists are minimally or unprotected road users. Their vulnerability results in a high injury risk despite their relatively low own speed. However, the actual injury situation of bicyclists has not been investigated very well so far. The purpose of this study was to analyze the actual injury situation of bicyclists in Germany to create a basis for effective preventive measures. Technical and medical data were prospectively collected shortly after the accident at the accident scenes and medical institutions providing care for the injured. Data of injured bicyclists from 1985 to 2003 were analyzed for the following parameters: collision opponent, collision type, collision speed (km/h), Abbreviated Injury Scale (AIS), Maximum AIS (MAIS), incidence of polytrauma (Injury Severity Score >16), incidence of death (death before end of first hospital stay). 4,264 injured bicyclists were included. 55% were male and 45% female. The age was grouped to preschool age in 0.9%, 6 to 12 years in 10.8%, 13 to 17 years in 10.4%, 18 to 64 years in 64.7%, and over 64 years in 13.2%. The MAIS was 1 in 78.8%, 2 in 17.0%, 3 in 3.0%, 4 in 0.6%, 5 in 0.4%, and 6 in 0.2%. The incidence of polytrauma was 0.9%, and the incidence of death was 0.5%. The incidence of injuries to different body regions was as follows: head, 47.8%; neck, 5.2%, thorax, 21%; upper extremities, 46.3%; abdomen, 5.8%; pelvis, 11.5%, lower extremities, 62.1%. The accident location was urban in 95.2%, and rural in 4.8%. The accidents happened during daylight in 82.4%, during night in 12.2%, and during dawn/dusk in 5.3%. The road situation was as follows: straight, 27.3%; bend, 3.0%; junction, 32.0%; crossing, 26.4%; gate, 5.9%; others, 5.4%. The collision opponents were cars in 65.8%, trucks in 7.2%, bicycles in 7.4%, standing objects in 8.8%, multiple objects in 4.3%, and others in 6.5%. The collision speed was grouped <31 in 77.9%, 31-50 in 4.9%, 51-70 in 3.7%, and >70 in 1.5%. The helmet use rate was 1.5%. 68% of the registered head injuries were located in the effective helmet protection area. In bicyclists, head and extremities are at high risk for injuries. The helmet use rate is unsatisfactorily low. Remarkably, two thirds of the head injuries could have been prevented by helmets. Accidents are concentrated to crossings, junctions and gates. A significant lower mean injury severity was observed in victims using separate bicycle lanes. These results do strongly support the extension or addition of bicycle lanes and their consequent use. However, the lanes are frequently interrupted at crossings and junctions. This emphasizes also the important endangering of bicyclists coming from crossings, junctions and gates, i.e. all situations in which contact of bicyclists to motorized vehicles is possible. Redesigning junctions and bicycle traffic lanes to minimize the possibility of this dangerous contact would be preventive measures. A more consequent helmet use and use and an extension of bicycle paths for a better separation of bicyclists and motorized vehicle would be simple but very effective preventive measures.
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.
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.
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.
During the last 5 years, the number of cars fitted with side airbags has dramatically increased. They are now standard equipment, even on many smaller cars or less luxurious vehicles. While some side airbags offer thoracic protection alone, there are those that combine thoracic and head protection (of which most deploy from the seat). Other systems employ separate airbags for head and thorax protection, which are designed to be effective noticeably in a crash against a pole. This paper proposes an evaluation of the effectiveness of side airbags in preventing thoracic injuries to passenger car occupants involved in side crashes. First, the target population (who can take benefit of side airbag deployment and in what circumstances) is defined. Side airbags can be especially effective in cases of impacts on the door with intrusion at a certain impact speed. Then, an example case of a side impact with side airbag deployment is given were side airbag deployment is thought to have had a positive effect on injury outcome. A further case is presented where the impact configuration is likely to have reduced the effect of side airbag deployment on injury outcome. Finally, the estimation of side airbag effectiveness (in terms of additional occupant protection brought exclusively by the airbag) is proposed by comparing injury risk sustained by occupants in (more or less) similar cars (fitted or non fitted with airbags) because, during these years, car structure, and side airbag conception have considerably evolved. In-depth accident data from France, the UK and Germany has been collected. Out of 2,035 side impact accident cases available in the databases, we selected 435 occupants of passenger cars (built from 1998 onwards) involved in an injury accident between year 1998 and year 2004 for EES (Energy Equivalent Speed) values between 20km/h and 50km/h. The occupants, belted or not, were sat on the struck side, whatever the obstacle and type of accidents (intersection, loss of control, etc.). For multiple impact crashes, the side impact is assumed to be the more severe one. Passenger cars were fitted with (96) or without (339) side airbags. Most of the potential risk explanatory variables were correctly and reliably reported in the databases (velocity " impact zone " impact angle " occupant characteristics, etc.). The analysis compared injury risks for different levels of EES and different types of side airbags. A logistic regression model was also computed with injury variables (such as thoracic AIS 2+ or AIS 3+) as the dependant variable and other variables (including airbag type and EES) as explanatory injury risk factors. Results revealed statistically non-significant reductions in thoracic AIS 2+ and AIS 3+ injury risk in side airbag equipped cars in the impact violence range selected (odds ratio between 0.84 and 0.98 depending on types of airbags). The results are discussed. The non-significance is assumed to be due to a low number of cases. Statistical analysis for head injuries was not possible due to the low number of accident cases with passenger cars fitted with head airbags in the databases. Moreover, the discrepancies between the data coming from different countries (especially calculation of EES) might have introduced instability in the analysis.
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.