81 Unfallstatistik
Pedestrian and cyclist are the most vulnerable road users in traffic crashes. One important aspect of this study was the comparable analysis of the exact impact configuration and the resulting injury patterns of pedestrians and cyclists in view of epidemiology. The secondary aim was assessment of head injury risks and kinematics of adult pedestrian and cyclists in primary and secondary impacts and to correlate the injuries related to physical parameters like HIC value, 3ms linear acceleration, and discuss the technical parameter with injuries observed in real-world accidents based documented real accidents of GIDAS and explains the head injuries by simulated load and impact conditions based on PC-Crash and MADYMO. A subsample of n=402 pedestrians and n=940 bicyclists from GIDAS database, Germany was used for preselection, from which 22 pedestrian and 18 cyclist accidents were selected for reconstruction by initially using PC-Crash to calculate impact conditions, such as vehicle impact velocity, vehicle kinematic sequence and throw out distance. The impact conditions then were employed to identify the initial conditions in simulation of MADYMO reconstruction. The results show that cyclists always suffer lower injury outcomes for the same accident severity. Differences in HIC, head relative impact velocity, 3ms linear contiguous acceleration, maximum angular velocity and acceleration, contact force, throwing distance and head contact timing are shown. The differences of landing conditions in secondary impacts of pedestrians and cyclists are also identified. Injury risk curves were generated by logistic regression model for each predicting physical parameters.
The accident research of Hanover and (from 1999 on) Dresden registered 736 leg injuries (AIS ≥ 2) from 1983 to March 2007. 174 of these injuries (23.6 %) were fractures or dislocations of foot and ankle. 149 feet of 141 front seat car occupants in 140 cars were affected. Of these 117 were drivers, 24 were front seat passengers. The mean age of occupants was 38.5 -± 16.8 years. Ankle fractures were the most frequent injury (n = 82; 80 malleolar fractures, 2 pilon fractures). 34 fractures and dislocations affected the hindfoot (5 talus and 26 calcaneal fractures, 2 subtalar dislocations and 1 subtotal amputation) , 16 to midfoot (4 navicular fractures, 5 cuboid fractures, 3 fractures of cuneiformia, 2 dislocations of chopart joint, 1 subtotal amputation, and one severe decollement) and 39 the forefoot (metatarsal fractures). Open fractures were seldom seen (2 malleolar fractures, 1 metatarsal fracture). Both feet were injured in 10 cases. 33 occupants (23.4 %) were polytaumatic had a polytrauma, 17 of them died. 81 percent of the occupants were belted. The cars were divided in pre EuroNCAP (year of manufacture 1997 and older) and post EuroNCAP cars (year of manufacture 1998 and newer). Most of the foot injuries were seen in pre EuroNCAP cars. Most of the occupants sat in compact cars (40 drivers and 9 front seat passengers) and large family cars (27 drivers and 7 co-drivers). 49 of 140 accidents occurred on country roads, 26 on main roads and 13 on motorways. The crash direction was mostly frontal. Generally were found no differences of delta v- and EES-level between the injured foot regions, but divided into pre- and post-EuroNCAP cars there was a tendency to higher delta v- and EES-levels in newer cars. The frequency of foot injuries increased linearly with increasing delta v-level; but above delta v-level of 55 km/h the linear increase only was seen in pre-EuroNCAP cars, post-EuroNCAP cars showed no further increase of injuries. The footwell intrusion showed no difference between the injured foot regions but pre-EuroNCAP cars had a tendency to higher footwell intrusion. There were no differences in footwell intrusion between the car types. Only 29 of 174 fractures or dislocations of foot were seen in post-EuroNCAP cars, the predominate number of these injuries (n = 145) were noticed in pre-EuroNCAP cars. A lower probability of long-term impairment was found in post-EuroNCAP cars for equal delta v levels, using the AIS2008 associated Functional Capacity Index (FCI) for the foot region.
Although ATV accidents account for numerous deaths in the US and Australia, the role in traffic accidents and hospital admissions in Germany is unknown. At a level I trauma centre, hospital and crash charts were analysed for medical and technical parameters of ATV accidents. ATV drivers were 0.1% of emergency trauma patients. The mean total hospital stayrnwas 15 days; there were 1.5 stays per patients with 2.0 surgical procedures needed. One patient died, only two recovered fully. 14 cases of ATV accidents out of 18990 (0.1%) were documented within 10 years. The mean impact velocity was 35 km/h. Car collisions were predominant. The upper extremity was the predominant injured region (AIS 0.7), Mean maximum AIS was 1.4. ATV accidents in Germany are rare but pose high risk for severe injuries. Possible reasons are low active and passive security, limited experience and risky driving behaviour. Preventive measures are discussed.rn
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.
Each year the traffic accident research teams in Dresden and Hanover provide an in-depth investigation of approximately two thousand accidents, aggregated in the GIDAS database. To accomplish a comprehensive review of each traffic accident recorded, a sensible and thorough encoding of suffered injuries is indispensable. The Abbreviated Injury Scale by AAAM offers a valuable and handy solution to achieve this goal. However, there were a few difficulties in the use of the AIS that came up in the past, which let to necessary improvements for the utilization of the AIS 2005 for GIDAS.
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.
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.
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.