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- Englisch (337) (entfernen)
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- Conference (253)
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- injury) (45)
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- Motorcyclist (27)
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- Accident reconstruction (26)
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- Geschwindigkeit (26)
- Impact test (veh) (26)
- Fahrerassistenzsystem (25)
- Speed (25)
- Insasse (23)
- Leistungsfähigkeit (allg) (23)
- Prüfverfahren (23)
- Test method (23)
- Active safety system (22)
- Driver assistance system (22)
- Test (22)
- PKW (21)
- Aktives Sicherheitssystem (20)
- Efficiency (20)
- Method (20)
- Passives Sicherheitssystem (20)
- Vehicle occupant (20)
- Risiko (19)
- Versuch (19)
- Passive safety system (18)
- Pkw (18)
- Verfahren (18)
- Interview (17)
- Benutzung (16)
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- Biomechanik (15)
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- Risikobewertung (15)
- Seitlicher Zusammenstoß (15)
- Motorcycle (14)
- Risk assessment (14)
- Safety belt (14)
- Side impact (14)
- Accident rate (13)
- Dummy (13)
- Leg (human) (13)
- Alte Leute (12)
- Auffahrunfall (12)
- Brustkorb (12)
- Fahrzeugsitz (12)
- Improvement (12)
- Rear end collision (12)
- Rechenmodell (12)
- Unfallhäufigkeit (12)
- Verbesserung (12)
- Überschlagen (12)
- Behaviour (11)
- Database (11)
- Development (11)
- Entwicklung (11)
- Mathematical model (11)
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- Schutzhelm (11)
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- Verhalten (11)
- Airbag (10)
- Berechnung (10)
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- Deformation (10)
- Fehler (10)
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- Krankenhaus (10)
- Menschlicher Faktor (10)
- Messung (10)
- Overturning (veh) (10)
- Thorax (10)
- Age (9)
- Alter (9)
- Bein (menschl) (9)
- Bremsung (9)
- Calculation (9)
- Error (9)
- Fahranfänger (9)
- Front (9)
- Hospital (9)
- Impact test (9)
- Japan (9)
- Prognose (9)
- Recently qualified driver (9)
- USA (9)
- Verformung (9)
- Wirbelsäule (9)
- Air bag (restraint system) (8)
- Braking (8)
- Digital model (8)
- Erste Hilfe (8)
- Lorry (8)
- Numerisches Modell (8)
- Prevention (8)
- Antikollisionssystem (7)
- Austria (7)
- Cervical vertebrae (7)
- Fracture (bone) (7)
- Halswirbel (7)
- Impact study (7)
- Interior (veh) (7)
- Knee (human) (7)
- Knochenbruch (7)
- Modification (7)
- Spinal column (7)
- Standardisierung (7)
- Vereinigtes Königreich (7)
- Veränderung (7)
- Österreich (7)
- Adolescent (6)
- China (6)
- Collision avoidance system (6)
- Compatibility (6)
- Cost benefit analysis (6)
- Driver training (6)
- EU (6)
- Fahrausbildung (6)
- Fahrzeuginnenraum (6)
- First aid (6)
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- Knotenpunkt (6)
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- Research report (6)
- Software (6)
- Standardization (6)
- Transport infrastructure (6)
- Vehicle regulations (6)
- Verminderung (6)
- Vorn (6)
- Wirksamkeitsuntersuchung (6)
- Wirtschaftlichkeitsrechnung (6)
- Analyse (Math) (5)
- Angle (5)
- Autobahn (5)
- Correlation (math, stat) (5)
- Decrease (5)
- Deformable barrier (impact test) (5)
- Delivery vehicle (5)
- Eins (5)
- Electronic stability program (5)
- Fahrstabilität (5)
- Forschungsarbeit (5)
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- Impact sled (5)
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- One (5)
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- Technologie (5)
- Technology (5)
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- Verkehrsinfrastruktur (5)
- Winkel (5)
- Abdomen (4)
- Aufprallschlitten (4)
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- Bremse (4)
- Classification (4)
- Coefficient of friction (4)
- Collision test (veh) (4)
- Damage (4)
- Deformierbare Barriere (Anpralltest) (4)
- Design (overall design) (4)
- Detection (4)
- Distraction (4)
- Driver information (4)
- Driving (veh) (4)
- Drunkenness (4)
- Dynamics (4)
- Dynamik (4)
- Einstellung (psychol) (4)
- Elektronisches Stabilitätsprogramm (4)
- Erziehung (4)
- Estimation (4)
- Fahrdatenschreiber (4)
- Fahrgeschicklichkeit (4)
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- Finite element method (4)
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- Motorway (4)
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- Occupant (veh) (4)
- Probability (4)
- Regression analysis (4)
- Regressionsanalyse (4)
- Reibungsbeiwert (4)
- Reproducibility (4)
- Reproduzierbarkeit (4)
- Sachschaden (4)
- Schutzeinrichtung (4)
- Schweden (4)
- Seite (4)
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- Sichtbarkeit (4)
- Straßenentwurf (4)
- Surface texture (4)
- Technische Vorschriften (Kraftfahrzeug) (4)
- Trunkenheit (4)
- Unfallfolgemaßnahme (4)
- United Kingdom (4)
- Unterleib (4)
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- Sichtbarkeit (4)
- Wahrscheinlichkeit (4)
- Woman (4)
- Ablenkung (psychol) (3)
- Anti locking device (3)
- Attitude (psychol) (3)
- Ausrüstung (3)
- Automatic (3)
- Autonomes Fahren (3)
- Autonomous driving (3)
- Befreiung (Bergung) (3)
- Bein (3)
- Bicycle (3)
- Blickfeld (3)
- Brake (3)
- Bus (3)
- Camera (3)
- Coach (3)
- Crash test (3)
- Czech Republic (3)
- Decision process (3)
- Detektion (3)
- Digitale Bildverarbeitung (3)
- Durability (3)
- Education (3)
- Effectiveness (3)
- Electric vehicle (3)
- Elektrofahrzeug (3)
- Entscheidungsprozess (3)
- Equipment (3)
- Event data recorder (road vehicle) (3)
- Extrication (3)
- Fahrrad (3)
- Field of vision (3)
- Gefahrenabwehr (3)
- Griffigkeit (3)
- Information documentation (3)
- Kamera (3)
- Kleidung (3)
- Korea (Süd) (Demokratische Republik) (3)
- Lieferfahrzeug (3)
- Lkw (3)
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- Mann (3)
- Medizinische Untersuchung (3)
- Methode der finiten Elemente (3)
- Norm (tech) (3)
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- Passenger (3)
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- Spain (3)
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- Specification (standard) (3)
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- Abbiegen (2)
- Abkommen von der Fahrbahn (Unfall) (2)
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- Begleitetes Fahren (2)
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- Compliance (specif) (2)
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- Edge (2)
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- Ergonomics (2)
- Ergonomie (2)
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- Eu (2)
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- Experience (human) (2)
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- Expertensystem (2)
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- Fahrsimulator (2)
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- Führerschein (2)
- Geländefahrzeug (2)
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- Langfristig (2)
- Learning (2)
- Long term (2)
- Luftverunreinigung (2)
- Medical examination (2)
- Messgerät (2)
- Methode der finite Elemente (2)
- Mobile phone (2)
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- Model (not math) (2)
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- Motorisierungsgrad (2)
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- Theorie (2)
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- (menschl) (1)
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- Active safety (1)
- Active safety system; Automatic; Brake; Car; Collision avoidance system; Conference; Driver assistance system; Germany; Impact test (veh); Rear end collision; Severity (accid (1)
- Activity report (1)
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- Conference; Germany; Injury; Medical examination; Spinal column; X ray (1)
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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.
A national initiative from the vehicle manufacturers, safety system suppliers, the road administration and universities in Sweden took off in 2007. The aim was to develop a national investigation network and a methodology focusing on all phases of a crash (pre-crash, in-crash and post-crash) as well as all parts of the road transport system (road user, vehicle and road environment). The initiative is formally run as a project with the acronym INTACT (Investigation Network and Accident Collection Techniques). It was a three year pilot with the aim to develop methodologies for an extended national crash investigation activity. During the first year the INTACT partners agreed on the aim for the investigation and methods for retrieving the data were developed. During the second and third year the methodology was tested in real-world investigations and further refinement was made. The paper describes the methodology developed to obtain high qualitative in-depth road crash data.
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.
The SafetyNet project was formulated in part to address the need for safety oriented European road accident data. One of the main tasks included within the project was the development of a methodology for better understanding of accident causation together with the development of an associated database involving data obtained from on-scene or "nearly onscene" accident investigations. Information from these investigations was complemented by data from follow-up interviews with crash participants to determine critical events and contributory factors to the accident occurrence. A method for classification of accident contributing factors, known as DREAM 3.0, was developed and tested in conjunction with the SafetyNet activities. Collection of data and case analysis for some 1 000 individual crashes have recently been completed and inserted into the database and therefore aggregation analyses of the data are now being undertaken. This paper describes the methodology development, an overview of the database and the initial aggregation analyses.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
The focus of the technical innovation in the automobile industry is currently changing to sensor based safety systems, which are operating in the pre-crash phase of an accident. To get more information about this pre-crash phase for real accidents a simulation of this phase using the GIDAS database is done. The basics for this simulation are geometrical information about the accident location and the exact accident data out of the GIDAS database. This aggregated information gives the possibility to simulate an exact motion for every accident participant, using MATLAB / SIMULINK, in the pre-crash phase. After the simulation the information about the geometrical positions, the velocities and maneuvers of the drivers to an individual TTC (time to collision) are available. With those results it is possible to develop new useful sensor geometries using pre-crash scatter plots or estimate the efficiency of implemented active safety systems in combination with sensor characteristics. This simulation can be done for every reconstructed accident included in the GIDAS database, so these results can represent a wide spread basis for the further development of active safety systems and sensor geometries and characteristics
Past European collaborative research involving government bodies, vehicle manufacturers and test laboratories has resulted in a prototype barrier face called the Advanced European Mobile Deformable Barrier (AE-MDB) for use in a new side impact test procedure . This procedure offers a better representation of the current accident situation and, in particular, the barrier concept is a better reflection of front-end stiffness seen in today- passenger car fleet compared to that of the current legislative barrier face. Based on the preliminary performance corridors of the prototype AE-MDB, a refined AE-MDB specification has been developed. A programme of barrier to load cell wall testing was undertaken to complete and standardise the AE-MDB specification. Barrier faces were supplied by the four leading manufacturers to demonstrate that the specification could be met by all. This paper includes background, specification and proof of compliance.
A set of recommendations for pan-European transparent and independent road accident investigations has been developed by the SafetyNet project. The aim of these recommendations is to pave the way for future EU scale accident investigation activities by setting out the necessary steps for establishing safety oriented road accident investigations in Member States. This can be seen as the start of the process for establishing road accident investigations throughout Europe which operate according to a common methodology. The recommendations propose a European Safety Oriented Road Accident Investigation Programme which sets out the procedures that need to be put in place to investigate a sample of every day road accidents. They address four sets of issues; institutional addressing the characteristics of the programme; operational describing the conditions under which data isrncollected; data storage and protection; and reports, countermeasures and the dissemination of data.rn
Road condition acquisition and assessment are the key to guarantee their permanent availability. In order to maintain a country's whole road network, millions of high-resolution images have to be analyzed annually. Currently, this requires cost and time excessive manual labor. We aim to automate this process to a high degree by applying deep neural networks. Such networks need a lot of data to be trained successfully, which are not publicly available at the moment. In this paper, we present the GAPs dataset, which is the first freely available pavement distress dataset of a size, large enough to train high-performing deep neural networks. It provides high quality images, recorded by a standardized process fulfilling German federal regulations, and detailed distress annotations. For the first time, this enables a fair comparison of research in this field. Furthermore, we present a first evaluation of the state of the art in pavement distress detection and an analysis of the effectiveness of state of the art regularization techniques on this dataset.
The national accident statistics demonstrate that the situation of passenger car side impacts is dominated by car to car accidents. Car side to pole impacts are relatively infrequent events. However the importance of car side to pole impacts is significantly increasing with fatal and seriously injured occupants. For the present study the German in-depth database GIDAS (German In-Depth-Accident Study) and the UK based database CCIS (Co-operative Crash Injury Study) were used. Two approaches were undertaken to better understand the scenario of car to pole impacts. The first part is a statistical analysis of passenger car side to pole impacts to describe the characteristics and their importance relevant to other types of impact and to get further knowledge about the main factors influencing the accident outcome. The second part contains a case by case review on passenger cars first registered 1998 onwards to further investigate this type of impact including regression analysis to assess the relationship between injury severity and pole impact relevant factors.