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Introduction: The method of causation analysis applied under the German accident survey GIDAS, which is based on Accident Causation Analysis System (ACAS) focuses on an on-scene data collection of predominantly directly event-related causation factors which were crucial in the accident emergence as situational resulting events and influences. The paradigm underlying this method refers to the findings of the psychological traffic accident research that most causally relevant features of the system components human, infrastructure and vehicle technology are found directly in the situation shortly before the accident. This justifies the survey method which is conducted directly at the accident (on-scene), shortly after the accident occurrence (in-time) with the detection of human-related causes (in-depth). Human aspects of the situation analysis that interact and influence the risk situations shortly before the collision are reported as errors, lapses, mistakes and failures in ACAS in specific categories and subcategories. Thus methodically ACAS is designed primarily for the collection of accident features on the level of operational action, which certainly leads to valid findings and behavioral causes of accidents. The enhancement by means of Moderating Conditions concerns the pre-crash phase in different levels: strategical, tactical and operational.
With an ever rising human life expectancy the share of elderly people in society is constantly rising. This leads to the fact that at the same rate the share of people with age related diseases such as dementia and poor eyesight taking part in traffic will rise and therefore traffic accidents caused by this group of people due to the disease will play an ever greater role. This Situation will be among the future challenges of road safety work. At present this study displays specific characteristics of accidents caused by elderly car drivers (aged 65 or higher) based on the analysis of the German In-Depth Accident Study GIDAS. Herein almost 1000 elderly car drivers were identified as accident participants in the years 2008 to 2011. The focus of this study lies on identifying special types of accidents which are caused by elderly drivers and on characterizing these types with the information gathered on scene and by interviewing the participants. The main evidence analyzed is the knowledge about the accident locality, the trajectories of the participants as well as the reasons for the occurrence of the accidents. Furthermore personal information such as the personal condition before the accident and driving purposes is used to identify patterns of contributing circumstances for accidents caused by elderly traffic participants.
Introduction: Spine injuries pose a considerable risk to life and quality of life. The total number of road deaths in developed countries has markedly decreased, e.g. in Germany from over 20000 in 1970 to less than 4000 in 2010, but little is known how this is reflected in the burden of spine fractures of motor vehicle users. In this study, we aimed to show the actual incidence of spine injuries among drivers and front passengers and elucidate possible dependencies between crash mechanisms and types of injuries.
From literature well-known analyzes on risks, hazards and causes of accidents of older drivers are amended by the present study in which a comparison of the specific features of accident causes of older car drivers (older than 60 years) and of younger car drivers (under 25 years) is conducted. Mainly the question is pursued if specific errors, mistakes and lapses are predominant in the two different age groups. The analysis system ACAS (Accident Causation Analysis System) used hereby consists of a sequential system of accident causation factors from the human, the technical and the infrastructural field, whereupon for this study the influence of the human features on the accident development in two different age groups is of interest. ACAS is both an accident model and an analysis and classification system, which describes the human participation factors of an accident and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. In five steps (categories) of a logical and temporal sequence the hierarchical system makes human functions and processes as determinants of accident causes identifiable. The methodology specifically focuses on the use in so-called "In-Depth" and "On-Scene" investigation studies. With the help of the system for each accident participant one or more of five hypotheses of human cause factors are formed and then specified by appropriate verification criteria. These hypotheses in turn are further specified by indicators in such manner that the coding of the causation factors by a code system meets the needs of database processing and are accessible to a quantitative data analysis. The first results of the descriptive comparison of the two age groups concern mainly differences in the functional levels "information admission/perception" (where the elderly drivers have more difficulties than the young ones) and "information processing/evaluation" (where the younger drivers show more problems). Concerning the cognitive function of "planning" the group of younger drivers seems to be more often involved in an accident because of excessive speed.
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.
Although the statistics show a decreasing rate of child injuries and fatalities in German road accidents more efforts can be made to protect children in cars e.g. by developing appropriate child restraint systems. An important part in of this work can be achieved with the help of crash tests using child dummies. However these crash tests cannot completely reflect the situation of real world crashes as factors like children moving out of the optimal position or children incorrectly fastened by their parents are difficult to predict. Therefore this study gives an overview over the current accident and injury situation of child occupants in cars in German road accidents.
The purpose of this study was to analyse the actual injury situation of bicyclists regarding accidents involving more than one bicyclist. Bicyclists were included in a medical and technical analysis to create a basis for preventive measures and discovered repeating accident patterns and circumstances such as daytime, environment, helmet use rate. Technical and medical data were collected at the scene, shortly after accident. The population was compared focusing on bicycle versus bicycle accidents. Technical analysis included speed at crash, type of collision, impact angle, environment, used lane and relative velocity. Medical analysis included injury pattern and severity (AIS, ISS). Included were 578 injured bicyclists in 289 accidents from years 1999 to 2008, 61 percent were male (n=350) and 39 percent female (n=228). Sixty-seven percent ranged between 18 to 64 years of age, twelve percent each between 13 to 17 years of age and older than 65 years, eight percent between 6 to 12 years and one percent between 2 to 5 years.. Crashes took place in urban areas in 92 percent, in rural areas in 8 percent. Weather conditions were dry lanes in 97 percent and wet conditions in 3 percent. Eighty-three percent of all accidents happened during daytime, ten percent during night, and seven percent during dawn. The helmet use rate was only 7,5 percent in all involved bicyclists. The mean Maximum Abbreviated injury scale, Injury severity score was 1,31. Bicyclists are still minimally- or unprotected road users. The helmet use rate is unsatisfactorily low. The incidence of bicycle to bicycle crashes is high. Most of these accidents take place in urban areas. The level and pattern of injuries is moderate. Most of the more severe injuries occur to the head and could have been avoided by frequent helmet use.
Accidents with vulnerable road users require special attention within the road safety work because these accidents are often accompanied with severe injuries. Thus In 2006 at least 6200 Powered Two Wheeler (PTW) riders were killed in road crashes in the EU 25 representing 16% of the total number of road deaths while accounting for only 2% of the total kilometers driven. For the prevention of accidents with VRU above all the knowledge of the causes of the accidents is of special importance. This study is based on the methodology of the German In-Depth Accident Study GIDAS. Within GIDAS extensive data on various fields of accidentology are collected on-scene from road traffic accidents with injuries in the Hannover and Dresden area. Using a well defined sample plan the collected data is highly representative to the whole German situation (Brühning et al, Otte et al). The need of in-depth accident causation data in accident research led to the development of a special tool for the collection of such data called ACASS (Accident Causation Analysis with Seven Steps), which was implemented in the GIDAS methodology in 2008 and described by Otte in 2009.
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