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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.
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.
Adverse weather could impair the performance of many important parts in road transportation. In a tropical country, the threats posed by the weather phenomenon can be viewed from a different perspective as the situation may not be as extreme as snow-related problems or excessive temperature in other countries. Specifically in Malaysia, the situation may be underestimated due to several reasons such as the deficiencies in accident reporting and lack of research work. This background research has looked into various publications as well as related data to explain the need of more comprehensive research in the future.
While accident statistics on a national level are provided by many countries, there is a need for international data that includes more detailed information about the accident, so called in-depth data. As a consequence, accident data projects have been emerging in different regions of the world. This creates a need for comparable and mergeable data from different countries, enabling the use of already existing accident data resources and helping to expedite the improvement of global road safety. While existing approaches focus that mostly on building a comprehensive accident database from scratch, the iGLAD project (Initiative for the Global Harmonization of Accident Data) attempts a more pragmatic approach by building on top of the work already accomplished in this area and complementing it. The target of iGLAD is to help setting up an additional dataset as a compatibility layer between already existing world wide data sets and integrating the structure of these by defining a common data scheme. This dataset is limited to the common denominator between the existing data sets and is inherently rather small and simple. Eventually, an individual converter for each participating accident investigation group will be built that enables pooling all data sets in a common repository. This not only saves costs and time, and hence makes such a target more feasible, but also creates data that is usable right from the start. This paper gives an overview of the current status of iGLAD and first steps taken. Additionally, some methodological aspects are discussed, next to a glance at other projects working currently on related issues, providing additional input for iGLAD. Finally, an overview of next steps and intended future work is given.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.
Nowadays human-created systems are increasing in complexity due to the interaction of humans and technology. Especially road traffic systems are composed of multitudinous resources (e.g. personnel, vehicles, organizations, etc.), which make it even harder to anticipate the positive and negative effects on safety. One key in achieving a significant reduction of fatalities is seen in driver assistant systems counterbalancing the lack of drivers' capabilities. But the actual outcome of implementing these sophisticated technologies especially on influencing driver's capabilities are yet unknown. Latest research exemplifies an increase of reaction times of drivers in case of dysfunctional driver assistant systems. This research paper applies STAMP/STPA (STAMP = systems-theoretic accident model and processes; STPA = systems-theoretic process analysis) to the German automobile traffic system focusing on the effects of driver assistant systems on drivers. By doing so, the potential hazards caused by technology can be identified.
Millions of kilometers are driven and recorded by car manufacturers and researchers every year to gather information about realistic traffic situations. The focus of these studies is often the recording of critical situations to create test scenarios for the development of new systems before introducing them into the market. This paper shows a novel Analysis and Investigation Method for All Traffic Scenarios (AIMATS) based on real traffic scenes. It also shows how to get detailed information about speeds, trajectories and behavior of all participants without driving thousands of kilometers at the example of conflict situations with animals. Basis of the AIMATS is the identification of the most relevant locations as "Points of Interest" (POI), the recording of the critical situations and their "base lines" at these POI. This paper presents a new method to identify critical scenarios involving both vehicles and animals as well as preliminary results of a study done in Saxony using this new method.
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.
There is a need for detecting characteristics of pedestrian movement before car-pedestrian collisions to trigger a fully reversible pedestrian protection system. For this purpose, a pedestrian sensor system has been developed. In order to evaluate the effectiveness of the sensor system, the in-depth knowledge of car-pedestrian impact scenarios is needed. This study aims at the evaluation of the sensor system. The accident data are selected from the STRADA database. The accident scenarios available in this database were evaluated and the knowledge of the most common scenarios was developed in terms of the pedestrian trajectory, the pedestrian speed, the car trajectory, the car velocity, etc. A mathematical model was then established to evaluate the sensor system with different detective angles. It was found that in order to detect all the pedestrians in the most common scenarios on time the sensor detective angle must be kept larger than 60 degrees.
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.