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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.
The national accident statistics demonstrate that the situation of passenger car side impacts is dominated by car to car accidents. Car side to pole impacts are relatively infrequent events. However the importance of car side to pole impacts is significantly increasing with fatal and seriously injured occupants. For the present study the German in-depth database GIDAS (German In-Depth-Accident Study) and the UK based database CCIS (Co-operative Crash Injury Study) were used. Two approaches were undertaken to better understand the scenario of car to pole impacts. The first part is a statistical analysis of passenger car side to pole impacts to describe the characteristics and their importance relevant to other types of impact and to get further knowledge about the main factors influencing the accident outcome. The second part contains a case by case review on passenger cars first registered 1998 onwards to further investigate this type of impact including regression analysis to assess the relationship between injury severity and pole impact relevant factors.
One goal of the assessment of the crashworthiness of passenger cars is to characterize the potential of injury outcome to occupants of cars involved in an accident. This can be achieved by the help of an index that puts the number of injured occupants of passenger cars in relation to the number of cars involved in an accident. As a consequence, this index decreases with a lower potential of injury and rises with a higher number of injuries while assuming a fixed number of accidents. Another index is introduced that uses an economical weighting of each injury level. The consequential injury costs are calculated using the average economical costs for lightly, severely and fatally injured persons. The calculation of the safety indices is based on an anonymized sample of accident data provided by the Federal Statistical Office. An index of Mercedes passenger car drivers depending on the year of registration between 1991 and 2006 is compared to the index of drivers of cars of other makes within the same range of registration years.
While many medical studies have dealt with the incidence, nature and treatment of polytrauma the injury-causing accident mechanisms are rarely discussed in detail, mostly due to the lack of documentation of the technical aspects. The present prospective study was started in late 2007 and collects data from traffic accidents with most severely injured in six south- German counties and two larger cities for the duration of one year. It is aimed at identifying and documenting all polytrauma cases (ISS ≥ 16) caused by traffic accidents and their crash circumstances. The data collection is based on an interdisciplinary concept to include both the police, emergency dispatch centers, hospitals and fire departments in the region and is completely anonymous. Potentially relevant cases where an emergency physician was called to the scene of a traffic accident are provided by the dispatch center. All three hospitals in the region suited for the treatment of polytraumatised patients record injuries, major diagnostic and surgery data. Data and images from the accident scene are provided by the police and by fire departments. The latter provide information which is usually not available from the police, like deployed airbags, vehicle extrication measures and detailed views of car interiors. The main objective of the study is to determine the structure of road users who sustain a polytrauma, their crash opponents and the injury patterns found in relation to the collision configuration and the protection by seat belts, air bags and other devices. With detailed documentation of vehicle damage and extrication measures the study is also intended to support the development of injury predictors for pre-hospital treatment and provide field data regarding further improvement of technical rescue.
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.
Today, Euro NCAP is a well established rating system for passive car safety. The significance of the ratings must however be evaluated by comparison with national accident data. For this purpose accidents with involvement of two passenger cars have been taken from the German National Road Accident Register (record years 1998 to 2004) to evaluate the results of the NCAP frontal impact test configuration. Injury data from both drivers involved in frontal car to car collisions have been sampled and have been compared, using a "Bradley Terry Model" which is well established in the area of paired comparisons. Confounders " like mass ratio of the cars involved, gender of the driver, etc. " have been accounted for in the statistical model. Applying the Bradley Terry Model to the national accident data the safety ranking from Euro NCAP has been validated (safety level: 1star <2 star <3 star <4 star). Significant safety differences are found between cars of the 1 and 2 star category as compared to cars of the 3 and 4 star category. The impact of the mass ratio was highly significant and most influential. Changing the mass ratio by an amount of 10% will raise the chance for the driver of the heavier car to get better off by about 18%. The impact of driver gender was again highly significant, showing a nearly 2 times lower injury risk for male drivers. With regard to the NCAP rating drivers of a high rated car are more than 2 times more probable (70% chance) to get off less injured in a frontal collision as compared to the driver of a low rated car.
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.
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.