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A total survey of road traffic accidents involving most severely injured, defined as sustaining a polytrauma or severe monotrauma (ISS > 15) or being killed, was conducted over 14 months in a large study region in Germany. Data on injuries, pre-clinical and clinical care, crash circumstances and vehicle damage were obtained both prospectively and retrospectively from trauma centers, dispatch centers, police and fire departments. 149 patients with a polytrauma and eight with a severe monotrauma were recorded altogether. 22 patients died in hospital. Another 76 victims had deceased at the accident scene. In 2008, 49 % of patients treated with life-threatening injuries were car or van occupants, 21 % motorcyclists, 18 % cyclists and 10 % pedestrians. Among fatalities at the scene, vehicle occupants constituted an even larger portion. The number of road users with life-threatening trauma in the region was extrapolated to the German situation. It suggests that 10 % among the "seriously injured" as defined in national accident statistics are surviving accident victims with a polytrauma or severe monotrauma.
The share of high-tensile steel in car bodies has increased over the last years. While occupant safety has generally benefited from this measure, there is a potential risk that, as a result, rescue time may increase considerably. In more than 60% of all car occupant fatalities a technical rescue has been necessary. These are in particular those cases where occupants die immediately at the accident scene. Therefore, in these cases "rescue time" is a very sensitive parameter. In addition to the general analysis of the need of technical rescue and the actual rescue time depending on model years, the injury pattern of occupants requiring technical rescue will be analysed to provide advice for rescue teams. Furthermore, a detailed analysis of rescue measures for the most popular car models depending on the safety cell design is given.
Since 2005, the motorcycle crash fatalities in the US exceeded 10% of the overall annual traffic fatalities. Consequently, it has become critical to gain in-depth understanding of the factors and characteristics contributing to motorcycle crashes. Unfortunately, there currently exists no database gathering the necessary information for an in-depth analysis of the US motorcycle crashes. So this study utilizes the NASS/CDS database (National Automotive Sampling System, Crashworthiness Data System) in order to gain insights into the patterns and factors leading to a NASS/CDS motorcycle crash, from 1997 to 2007. NASS/CDS samples about 5,000 passenger car tow-away crashes per year. Each case includes photographs and detailed data on crash and pre-crash characteristics, vehicle types, trajectories, types of impact, and other pertinent roadway and crash scene information, allowing an in-depth investigation of the crash mechanisms. However, the NASS/CDS sampling process specifically focuses on passenger car crashes, so the cases extracted only correspond to crashes in which a passenger vehicle was towed, and a motorcycle was somehow involved. Thus, a by-hand in-depth review of about 200 cases allowed retrieving 106 relevant crashes for this study, tending to represent the severe passenger vehicle(s) versus motorcycle(s) crashes on US roads. The findings lead to the conclusion that these crashes mostly result from the low conspicuity of the motorcycle, and from the inability of the car drivers to fully appreciate and anticipate the behavior of a motorcycle. Indeed, it has been shown that, first, the car drivers involved in these cases did not attempt any avoidance maneuver, second, they were largely of ages under 25, and finally, the majority of the crashes were in an intersection scenario. In addition, the two major scenarios unveiled were the car attempting a left turn from the opposite direction and the car attempting a left turn from the right. The paper mentions several solutions to enhance the motorcycle- conspicuity and to allow the car drivers to better anticipate its behavior, which seem to be key factors in the intersection-related crashes (and more generally in the passenger vehicle(s) versus motorcycle(s) crashes).
Real world accident reconstruction with the Total Human Model for Safety (THUMS) in Pam-Crash
(2013)
Further improvement of vehicle safety needs detailed analysis of real world accidents. According to GIDAS (German In-Depth Accident Study) most car to car front accidents occur at mid-crash severity. In this range thoracic injuries already occur. In this study a real world frontal crash with mid-crash severity out of the AARU database was reconstructed. The selected car to car accident was reconstructed by AARU by means of pc-crash software in order to get the initial dynamic accident conditions. These initial conditions were used to reconstruct the complete accident in more detail using FE models for the car structure and the occupants. Occupant simulations were performed with FE HIII-dummy models and the THUMS using Pam-Crash code. An initial THUMS validation was performed in order to verify the model-´s biofidelity by means of table-top test simulations. THUMS bone stiffness values were modified to match the real word occupant age. A comparison between driver and passenger restraint system loading was done, as well as an injury prediction comparison between the HIII-dummy model and THUMS response for both cases. Detailed comparison between the HIII-dummy models and THUMS regarding thoracic loading are discussed.
Injury severity of e.g. pedestrians or bikers after crashes with cars that are reversing is almost unknown. However, crash victims of these injuries can frequently be seen in emergency departments and account for a large amount of patients every year. The objective of this study is to analyze injury severity of patients that were crashed into by reversing cars. The Hannover Medical School local accident research unit prospectively documented 43,000 road traffic accidents including 234 crashes involving reversing cars. Injury severity including the abbreviated injury scale (AIS) and the maximum abbreviated injury scale (MAIS) was analyzed as well as the location of the accident. As a result 234 accidents were included into this study. Pedestrians were injured in 141 crashes followed by 70 accidents involving bikers. The mean age of all crash victims was 57 -± 23 years. Most injuries took place on straight stretches (n = 81) as well as parking areas (n = 59), entries (n = 36) or crossroads (n = 24). The AIS of the lower extremities was highest followed by the upper extremities. The AIS of the neck was lowest. The mean MAIS was 1.3 -± 0.6. The paper concludes that the lower extremities show the highest risk to become injured during accidents with reversing cars. However, the risk of severe injuries is likely low.
This study aimed at prediction of long bone fractures and assessment of lower extremity injury mechanisms in real world passenger car to pedestrian collision. For this purpose, two pedestrian accident cases with detail recorded lower limb injuries were reconstructed via combining MBS (Multi-body system) and FE (Finite element) methods. The code of PC Crash was used to determine the boundary conditions before collision, and then MBS models were used to reproduce the pedestrian kinematics and injuries during crash. Furthermore, a validated lower limb FE model was chosen to conduct reconstruction of injuries and prediction of long bone fracture via physical parameters of von Mises stress and bending moment. The injury outcomes from simulations were compared with hospital recorded injury data and the same long bone fracture patterns and positions can be observed. Moreover, the calculated long bone fracture tolerance corresponded to the outcome from cadaver tests. The result shows that FE model is capable to reproduce the dynamic injury process and is an effective tool to predict the risk of long bone fractures.
India is one of the leading countries reporting highest road accidents & related injuries. TMARG (Tata Motors Accident Research Group) has been recording crashes in association with M/s. Lokamanya Medical Foundation since 2011 with M/s, Amandeep Hospitals since Aug 2013. This study has highlighted some accident types not discussed extensively in literature. Trucks to Truck impacts " Cabin interaction with overhanging loadbody structures and Offset underside impacts for passenger vehicles are seen in significant numbers. The paper discusses these in more detail including severity.
This study aimed at comparing head Wrap Around Distance (WAD) of Vulnerable Road User (VRU) obtained from the German in-depth Accident Database (GIDAS), the China in-depth Accident Database (CIDAS) and the Japanese in-depth Accident Database (ITARDA micro). Cumulative distribution of WAD of pedestrian and cyclist were obtained for each database (AIS2+) showing that WAD of cyclists were larger than the ones of pedestrians. Comparing three regions, the 50%tile WAD of GIDAS was larger than that of both Asian accident databases. Using linear regression that might predict WAD of pedestrians and cyclists from Impact speed and VRU height, WADs were calculated to be 206cm/219cm (Pedestrian/Cyclist) for GIDAS, 170cm/192cm for CIDAS and 211cm/235cm for ITARDA. In addition, this study may be helpful for reconsideration of WAD measurement alignment between accident reconstruction and test procedures.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
The paper gives an overview of the recent (mostly 2012) figures of killed bus/coach occupants (drivers and passengers) in 27 Member States of the European Union as reported by CARE. The Evolution of the figures of bus/coach occupants killed in road accidents urban, rural without motorway and on motorways from 1991 to 2010 in 15 Member States of the EU supplements this information. More detailed are the figures reported for Germany by the Federal Statistics. The paper displays long-term evaluations (1957 to 2012) for killed, seriously and slightly injured occupants in all kinds of buses/coaches. Midterm evaluations (1995 to 2012) of the figures of fatalities and casualties are displayed for different busses according to their identification of road using as coaches, urban buses, school buses, trolley buses and "other buses". To be able to compare the evolutions of the safety of vehicle occupants it is customary to use different risk indicators. Calculations and illustrations for three often used indicators with their development over time are given: fatalities, seriously injured and slightly injured per 100,000 vehicles registered, per 1 billion (109) vehicle-kilometres travelled and per 1 billion (109) person-kilometres. These indicators are shown for occupants of cars, goods vehicles and buses/coaches. For the period from 1957 until 2012 it is obvious, that for all three vehicle categories analysed there was a clear long-term trend towards more occupant safety in terms of casualties per vehicles registered and per vehicle mileage. This was most significant for car occupants but it can be seen for bus/coach occupants and goodsvehicle occupants as well. Figures of killed occupants and of casualties related to person-kilometres are calculated and displayed for the shorter period 1995 to 2012. Here it becomes obvious that the bus/coach is still the safest mode of transport for the occupants of road vehicles. Graphs for the casualty risk indices still show significantly higher risks for car occupants despite the corresponding curve moved sustainable downwards. It is remarkable, that the risks of being killed or injured for the occupants of urban buses is growing whereas the corresponding risk for the occupants of coaches in line traffic tends downwards. The article ends with a short comparison and discussion of the risk indicators which are actually published for the occupants (driver and passengers) of cars and the passengers of buses/coaches, railroads, trams and airplanes. The interpretation of such information depends on the perception and it seems that for a complete view not only one indicator should be used and the evolutions of the indicator values during longer periods (as displayed with examples in the paper) should also be taken into account.