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The European Enhanced Vehicle-safety Committee wants to promote the use of more biofidelic child dummies and biomechanical based tolerance limits in regulatory and consumer testing. This study has investigated the feasibility and potential impact of Q-dummies and new injury criteria for child restraint system assessment in frontal impact. European accident statistics have been reviewed for all ECE-R44 CRS groups. For frontal impact, injury measures are recommended for the head, neck, chest and abdomen. Priority of body segment protection depends on the ECE-R44 group. The Q-dummy family is able to reflect these injuries, because of its biofidelity performance and measurement capabilities for these body segments. Currently, the Q0, Q1, Q1.5, Q3 and Q6 are available representing children of 0, 1, 1.5, 3 and 6 years old. These Q-dummies cover almost all dummy weight groups as defined in ECE-R44. Q10, representing a 10 year-old child, is under development. New child dummy injury criteria are under discussion in EEVC WG12. Therefore, the ECE-R44 criteria are assessed by comparing the existing P-dummies and new Q-dummies in ECE-R44 frontal impact sled tests. In total 300 tests covering 30 CRSs of almost all existing child seat categories are performed by 11 European organizations. From this benchmark study, it is concluded that the performance of the Q-dummy family is good with respect to repeatability of the measurement signals and the durability of the dummies. Applying ECE-R44 criteria, the first impression is that results for P- and Q-dummy are similar. For child seat evaluation the potential merits of the Q-dummy family lie in the extra measurement possibilities of these dummies and in the more biofidelic response.
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.
The overall purpose of the ASSESS project is to develop a relevant and standardised set of test and assessment methods and associated tools for integrated vehicle safety systems, primarily focussing on currently available pre-crash sensing systems. The first stage of the project was to define casualty relevant accident scenarios so that the test scenarios will be developed based on accident scenarios which currently result in the greatest injury outcome, measured by a combination of casualty severity and casualty frequency. The first analysis stage was completed using data from a range of accident databases, including those which were nationally representative (STATS19, UK and STRADA, SE) and in-depth sources which provided more detailed parameters to characterise the accident scenarios (GIDAS, DE and OTS, UK). A common analysis method was developed in order to compare the data from these different sources, and while the data sets were not completely compatible, the majority of the data was aligned in such a way that allowed a useful comparison to be made. As the ASSESS project focuses on pre-crash sensing systems fitted to passenger cars, the data selected for the analysis was "injury accidents which involved at least one passenger car". The accident data analysis yielded the following ranked list of most relevant accident scenarios: Rank Accident scenario 1 Driving accident - single vehicle loss of control 2 Accidents in longitudinal traffic (same and opposite directions) 3 Accidents with turning vehicle(s) or crossing paths in junctions 4 Accidents involving pedestrians The ranked list highlights the relatively large role played by "accidents in longitudinal traffic", and "accidents with turning vehicle(s) or crossing paths in junctions" (the second and third most prevalent accident scenarios, respectively). The pre-crash systems addressed in ASSESS propose to yield beneficial safety outcomes with specific regard to these accident scenarios. This indicates that the ASSESS project is highly relevant to the current casualty crash problem. In the second stage of the analysis a selection of these accident scenarios were analysed further to define the accident parameters at a more detailed level .This paper describes the analysis approach and results from the first analysis stage.
This study investigates the protection offered by passive head-restraints with different stiffness and energy dissipation properties. For this purpose, computational multi-body models of a generic car seat and a biofidelic 50thpercentile male human for rear impact are used to study different seat designs and passive head-restraints. The validated seat-occupant model is also used in the design of two different car-seat models which are shown to effectively mitigate whiplash by utilising a crash-energy distribution technique. Five different passive head-restraints with varying stiffness (low-medium-high) and energy dissipation percentages (low-high) are successively attached to four different car-seat models. The simulation results indicate that the protection offered by head restraints is strongly dependent on the seat design. It has also been shown that the stiffness of the passive head-restraint has much more influence on whiplash-risk in comparison to its energy dissipation capacity.
Das Führen von Kraftfahrzeugen der Klasse 2 ist entsprechend der Fahrerlaubnisverordnung nach mehr als zwei epileptischen Anfällen ausgeschlossen. Als Ausnahme gilt eine durch ärztliche Kontrolle nachgewiesene fünfjährige Anfallsfreiheit ohne antiepileptische Behandlung. Im vorliegenden Fall wies ein Lkw-Fahrer mindestens vier epileptische Anfälle auf, eine fünfjaehrige Anfallsfreiheit ohne Medikamente unter ärztlicher Kontrolle ließ sich nicht feststellen. Der letzte Anfall führte zu einem Verkehrsunfall mit anschließendem Gerichtsverfahren. Ursächlich für den Unfall war am ehesten die abgesetzte Medikation. Ein Verfahren hinsichtlich der Ungeeignetheit zum Führen von Kraftfahrzeugen der Klasse 2 wurde eingeleitet.
Accident research 2.0: New methods for representative evaluation of integral safety in traffic
(2013)
BMW has developed a procedure for rating Advanced Driver Assistance Systems (ADAS) benefits that integrates two distinct tools. The tool "S.A.F.E.R." is designed to analyze the pre-crash phase. The aim of S.A.F.E.R. is to simulate all relevant processes in sufficient detail to obtain reproducible estimates of key indicators (effectiveness, false positives, etc.). The relevant processes include not only traffic and vehicle dynamics, but also environmental and most importantly human factors. Representative distributions of factors and parameters are obtained by taking the stochastic variation of all relevant parameters into account in the simulations. The second tool, known as "ICOS", has been designed to provide a high-resolution, high-fidelity description of crash phase dynamics. If one converts the outputs of stochastic simulation into inputs for crash dynamics, the result is a comprehensive description of exactly how a safety system can reduce injuries. Applications currently focus on high-fidelity simulation of individual crashes in order to enhance our understanding and optimization of connected safety systems. An integrated simulation process thus allows an exact prediction of the effectiveness in individual cases in terms of injury severity. The development and rating of integral safety need to reflect the true efficiency in the field. The integrated approach described here could provide a valid and reproducible basis for rating connected systems of active and passive safety. In particular, "virtual experiments" using a traffic-based approach and incorporating models of all relevant processes constitute an essential element of the approach.
In order to improve the protection of children transported in cars, within the CHILD programme (GR3D-CT2002-00791) real world road accidents are thoroughly analysed and then reconstructed in laboratory. Prior to comparing injury severities of real victims to physical parameter values measured on the dummies, the quality of the reconstructions is evaluated by experts who use their experience based on the investigation of numerous and various accidents. This paper presents a new tool aiming at better evaluating and validating accident reconstructions. It is based on statistical evaluation of vehicle deformations which gives weighing factors for every part of the car body structure finally leading to a specific Reconstruction Quality Score (RQS indicator). Furthermore, the reliability of this score, depending on the number of measured points, can be established. This tool includes a function aiming at adjusting the speed for a further reconstruction and at defining the launching speed and the pulse shape for complementary sled tests. Finally, the functions of the RQS software and database are presented.
Whiplash injuries are characterized by the high variability of its symptoms and by the subjectivity of its diagnosis, which sometimes leads to frauds perpetrated by victims of rear-end impacts. It is estimated that whiplash injuries cost annually about 10.000 million Euros in Europe. Therefore, the aim of this study was to investigate the influence of the dynamics of the accident in which the victim was involved in the probability of development of whiplash associated injuries. In the presented methodology, first an accident reconstruction is performed where the dynamics of the accident is determined. This is carried out using the software PC-Crash, police and insurance companies' data. Then biomechanical injuries criteria related with whiplash injuries are evaluated. For the evaluation of the probability of having whiplash injuries, the Neck Injury Criterion (NIC) of the victim and the mean acceleration of the vehicle were evaluated. Then, with medical reports, the results of the accident reconstruction are correlated with the reported injuries. Some examples are presented. The results obtained indicate that the study of the dynamics of the road accidents in which the victims were involved could be used as an auxiliary of the prognosis of whiplash injuries and is important for a precise diagnosis of this type of injuries.
Road safety is a major preoccupation of the European Commission and the road transport industry and depends on numerous significant factors. In order to improve road safety and to plan effective safety improvement actions for truck transport, we must first identify the problems to be addressed, i.e. what are the main causes of truck accidents. The ETAC project, initiated by the European Commission and the IRU, was launched in order to set up a heavy goods vehicle accident causation study across European countries to identify future actions which could contribute to the improvement of road safety. The results will be based on a detailed analysis of truck accident data collected in seven European countries according to a common methodology which has been elaborated through numerous national and European projects. This paper describes the common methodology used to collect the information on the scene of the accident and to analyse the data so that the reconstruction of the crash events may be carried out. CEESAR proposes a methodology using its experience gained from over 10 years of accident data collection. This methodology is based on an in-depth investigation of the parameters involved in-an accident and linked to the driver, the vehicle, the road and their environment. In-depth investigation requires accident investigator presence on the scene of the accident in order to collect volatile information such as marks on the road, weather conditions, visibility, state and equipment of the vehicle, driver interview. Later, passive and active information is gathered, either at the hospital for the driver, at the garage for the vehicle or on the spot for the road geometry. A reconstruction carried out with the help of specific software and the analysis of the data collected and calculated enables the identification of the main causes of the accident and the future actions to plan in order to improve road safety as regards truck traffic.