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Injury probability functions for pedestrians and bicyclists based on real-world accident data
(2017)
The paper is focusing on the modelling of injury severity probabilities, often called as Injury Risk Functions (IRF). These are mathematical functions describing the probability for a defined population and for possible explanatory factors (variables) to sustain a certain injury severity. Injury risk functions are becoming more and more important as basis for the assessment of automotive safety systems. They contribute to the understanding of injury mechanisms, (prospective) evaluation of safety systems and definition of protection criteria or are used within regulation and/or consumer ratings. In all cases, knowledge about the correlation between mechanical behavior and injury severity is needed. IRFs are often based on biomechanical data. This paper is focusing on the derivation of injury probability models from real world accident data of the GIDAS database (German In-depth Accident Study). In contrast to most academic terms there is no explicit term definition or definition of creation processes existing for injury probability models based on empirical data. Different approaches are existing for such kind of models in the field of accident research. There is a need for harmonization in terms of the used methods and data as well as the handling with the existing challenges. These are preparation of the dataset, model assumptions, censored/unknown data, evaluation of model accuracy, definition of dependent and independent variable, and others. In the presented study, several empirical, statistical and phenomenological approaches were analyzed regarding their advantages and disadvantages and also their applicability. Furthermore, the identification of appropriate prediction parameters for the injury severity of pedestrians has been considered. Due to its main effect on injuries of pedestrians and bicyclists, the importance of the secondary impact has also been analyzed. Finally, the model accuracy, evaluated by several criteria, is the rating factor that gives the quality and reliability for application of the resulting models. After the investigation and evaluation of statistical approaches one method was chosen and appropriate prediction variables were examined. Finally, all findings were summarized and injury risk functions for pedestrians in real world accidents were created. Additionally, the paper gives instructions for the interpretation and usage of such functions. The presented results include IRFs for several injury severity levels and age groups. The presented models are based on a high amount of real world accidents and describe very well the injury severity probability of pedestrians and bicyclists in frontal collisions with current vehicles. The functions can serve as basis for the evaluation of effectiveness of systems like Pedestrian-AEB or Bicycle-AEB.
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.
The Traffic Accident Research Institute at University of Technology Dresden investigates about 1,000 accidents annually in the area around and in Dresden. These datasets have been summarized and evaluated in the GIDAS (German Accident In-Depth Study) project for 13 years. During the project it became apparent that the specific traffic situation of a covert exit of a passenger car and an intersecting two-wheeler involves a high risk potential. This critical situation develops in a large part due to the lack of visibility between the driver and the intersecting bike. In this paper the accident avoidance potential of front camera systems with lateral field of view, which allows the driver to have an indirect sight into the crossing street area will be presented.
The declining trend since 1991 in the number of killed people was broken in 2011 when overall 4 009 people died in traffic accidents in Germany. The question arises if there is a stagnating trend of fatalities in Germany in future? By breaking down the accidents with casualties towards a monthly view one can see a decreasing trend of fatalities in the warmer months especially since 2009. When comparing against winter months higher deviations are observed. In December 2011 an increase of 191 traffic deaths were registered (181 in 2010 compared to 372 in 2011). Further analyses of different accident influences were evaluated and their possibility of drastic change from one year to the other was determined. As seen weather- and environmental conditions are one of the major contributing factors and are one of the causes for the increased number of fatalities. To support the underlying assumption a model had been created to calculate the number of traffic deaths on a daily basis approach. As an input, road conditions projected through weather parameters and also different driving behaviors on weekdays or holidays were used. As a result, estimates of daily fatality with up to 75% precision can be achieved out of the 2009, 2010 and 2011 data. Further on it shows that weather and street conditions have a high influence on the overall resulting number of traffic accidents with casualties, and especially to the number of fatalities. Hence it is estimated that approximately 3 300 people were killed in traffic accidents in Germany in 2013 which would be again a reduction of another 13% compared to 2012. Therefore an answer to the question will be that the decreasing trend in traffic fatalities in Germany somehow is not broken when environmental conditions are included in national statistics. Their effects will become more visible in future accident statistics and it is estimated variances of 5% to 8% of the annual number of traffic fatalities in Germany will be seen.
Side impacts, both nearside and farside, have been indicated by research to be responsible for a large proportion of serious injuries from road crashes. This study aimed to compare and contrast the characteristics of nearside and farside crashes in Australia, Germany and the U.S., using the ANCIS, GIDAS and NASS/CDS in-depth-databases, in order to establish the impact and injury severity associated with these crashes, and the types of injuries sustained. The analyses revealed some interesting similarities, as well as differences, between both nearside and farside crashes, and the emergent trends between the three investigated countries. More specifically, it was indicated that whilst the severity of injury sustained in nearside crashes was slightly greater overall than that found for farside crashes, careful consideration of struck and nonstruck side occupants must be made when considering aspects such as vehicle design and occupant protection.
When assessing the consequences of accidents normally the injury severity and the damage costs are considered. The injury severity is either expressed within the police categories (slight injury, severe injury or fatal injury) or the AIS code that rates the fatality risk of a given injury. Both injury metrics are assessing the consequences of the accident directly after the accident. However, not all consequences of accidents are visible directly after the accident and the duration of the consequences are different. Besides a physiological reduction of functionality social and psychological implications such as reduced mobility options, problems to continue the original job etc. are happening. In order to assess long term consequences of accidents the MHH Accident Research Unit established a brief questionnaire that is distributed to accident involved people of the Hannover subset of the GIDAS data set approx. one year after the accident beginning with the accident year 2013. The basic idea of using a brief questionnaire (in fact only one page) is to obtain a relatively large return rate because the questionnaire appears to be simple and quickly answered. This appears to be important because it is believed that the majority of accident involved people will not report long term consequences. In order to allow a more detailed survey amongst those responders that are reporting long term consequences they are asked for a written consent for the additional questionnaire that will be distributed at a time that is not yet defined. Long term consequences are reported for all addressed areas, medical, physiological, psychological and sociological by people without injuries, with minor injuries and with severe injuries.
The grip between the road surface and vehicle tires is the physical basis for the moving of all vehicles in road traffic. In case of an accident the available grip level is one of the most relevant influence factors, influencing the causation and the procedure of the accident. However, the estimation of the grip level is not easy and therefore, is commonly not done on the accident scene. This is especially true for the measurement of the water depth. Until now, real accident databases provide no measurement data about the grip level and the water film depth and thus, the estimation of its influence is not possible yet. From the tyre manufacturers point of view, it is important to know about the road conditions (namely grip level, macro-texture, water depth, temperature) at the accident scene, as well as the operating conditions of the vehicles (braking, loss of control, speed, etc). These data is necessary to define relevant tyre traction tests for the end-user and for regulations. For this reason VUFO and Michelin developed a consistent method for the measurements of grip level and water depth for the accidents of the GIDAS database. The accident research team of Dresden, which documents about 1000 accidents with at least one injured person every year, is measuring the micro-roughness and the macro-roughness directly on the spot. For the measurement of the micro-roughness a Skid Resistance Tester (British Pendulum) is used. The Mean Texture Depth (describing the macro-roughness) is measured by the Sand Depth Method. Since June 2009, measurements for more than 700 accidents including 1200 participants have been carried out. In case of wet or damp road conditions during the accident, the water depth is measured additionally. Therefore VUFO and Michelin developed a special measurement device, which allows measurements with an accuracy of 1/10 millimetre. The measurement point at the accident scene is clearly defined and thus, the results are comparable for all different accidents and participants. The use of the GIDAS database and the accident sampling plan allows representative statements for the German accident scenario. With this data it is possible for the first time to have an accurate view of the road conditions at the accident scene. One possibility is a more detailed estimation of hydroplaning accidents using the actually measured water depths. The development of new testing methods and new tires can be based on the real situation of the road infrastructure. Furthermore, the combination of the technical GIDAS data and the measured road surface properties can also be used for the estimation of effectiveness of several safety systems like the brake assist and/or emergency braking systems. The calculation of a reduced collision speed due to the use of a brake assist is only one example for the application of real measured grip level data.
Supervision of the safety performance in public transport is one of the main tasks of the Federal Office of Transport (FOT) in Switzerland. Recently a three level system of safety indicators has been defined to cover all means of Swiss public transport. The safety indicators are fed by the FOT incident database since the year 2000. In cooperation with the Institute for Traffic Safety and Automation Engineering (iVA) at TU Braunschweig, Germany, FOT is developing a suitable methodology for the definition and evaluation of the safety targets in Swiss public transport. The methodology is applied for evaluation of safety indicators on a country level and for single transport companies. In a new approach the abovementioned methodology is applied to car incident data to develop an indicator based cross-modal safety measure.
Having a look at safety to traffic and the prevention of accidents it can be observed that technical improvements in active safety of vehicles have let to various positive effects in this area. Among other components the tyre-road-contact takes a key role in the development of active safety technologies. All forces in accelerating, breaking and vehicle guidance have to be transmitted through the tyre-road contact area by friction forces. A common way to characterize a friction process is to identify the coefficient of friction μ between two touching materials. Even though there are several approaches to experimentially characterise road surfaces, no standard method exists. In this paper an overview of existing test methods is given. Furthermore the preliminary design of a newly developed portable test device with its possibility to investigate the tyre-road-friction of arbitrary roads or even places of accidents is shown.
Motorcycle crashes in Austria: Analysis of causes and contributing factors based on in-depth data
(2017)
From CEDATU, the in-depth accident database run by the Vehicle Safety Institute at Graz University of Technology, a representative sample of 101 crashes involving at least one motorcycle was selected. The analysis focused on causes for crashes as well as on contributing factors, but also included parameters of road, riders and vehicles. Own riding speed and "unexpectable action by another road user" were the most frequent causes for accidents. Inappropriate safety distance or delayed reaction were frequent, both as causation factors and as contributing factors. Infrastructure issues never cause an accident, but they are very frequent as contributing factors; road geometry and road guidance are by far most frequent among these. This paper also discusses accidents by type and other parameters (e.g. injury severity by body region, collision speed, age and others), and compares accident causes to previous studies as well as the police reported accident statistics.