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This study aimed at comparing head Wrap Around Distance (WAD) of Vulnerable Road User (VRU) obtained from the German in-depth Accident Database (GIDAS), the China in-depth Accident Database (CIDAS) and the Japanese in-depth Accident Database (ITARDA micro). Cumulative distribution of WAD of pedestrian and cyclist were obtained for each database (AIS2+) showing that WAD of cyclists were larger than the ones of pedestrians. Comparing three regions, the 50%tile WAD of GIDAS was larger than that of both Asian accident databases. Using linear regression that might predict WAD of pedestrians and cyclists from Impact speed and VRU height, WADs were calculated to be 206cm/219cm (Pedestrian/Cyclist) for GIDAS, 170cm/192cm for CIDAS and 211cm/235cm for ITARDA. In addition, this study may be helpful for reconsideration of WAD measurement alignment between accident reconstruction and test procedures.
Pedestrians represent about 20% of the overall fatalities in Europe- road traffic accidents. In this paper a methodology is proposed to understand why the numbers are so high, especially in the south of Europe and particularly in Portugal, . First a detailed statistical analysis using Ordinal Logistic Regression model (OLR) was applied to the gathered data from all Portuguese accidents with victims in the period 2010-2012. In a second stage accident reconstruction computational techniques using pedestrian biomechanical models are used to evaluate the accident conditions that lead to the injuries, such as the speed and the impact location. For biomechanical injury criterions, the AIS (Abbreviated Injury Scale), the HIC (Head Injury Criterion) and other injury criterions based on the resulting accelerations in the pedestrian's body are used. The statistical model reported that there were several predictors that significantly influenced the pedestrian injury severity in the event of a road accident, such as Pedestrian's age, Pedestrian's gender, Vehicle Design/Category or Driver's gender. The use of injury scales and biomechanical criterions in in-depth investigation of road accidents, such as AIS, can significantly improve the quality of the reconstruction process.
The current Brussels EU Regulation No. 1235/2011, valid from May 30, 2012, has introduced an European Tyre Label with wet grip index G classes from A to G for passenger car tyres C1, light commercial vehicles tyres C2 and heavy truck- and bus tyres C3. Every wet grip class for each vehicle category has a defined band of numerical values for the wet grip index G. The legislated wet grip values G in this EU- Regulation are very low. The measured braking distances and corresponding impact speeds of the test vehicles are showing very critical results. Regulation No. 1235/2011 of the European Parliament and the Council for Type Approval of Vehicles (EU) should be changed in such a way, that for C1-tyres (normal passenger cars tyres) the minimum wet grip index G is 1.25. All C2-tyres (light commercial vehicles tyres) should at least meet a minimum wet grip index of G = 1.1. All C3-tyres (heavy trucks and buses tyres) should at least meet a minimum wet grip index of G = 0.95. Due to the missing lower limits for G in the wet grip class F for C1, C2 and C3 tyres according to Commission Regulation (EU) No. 1235/2011, officially valid from 30 May 2012, a tyre-to-road coefficient of adhesion in the extreme of 0 (zero) is legally permitted. This is an apparent flaw in above cited EU Regulation, which causes a potential danger to the road traffic safety for all motor vehicles in Europe with such tyres. The wet grip class F has to be removed urgently from said EURegulation, since a direct liability of the responsible EU-Commission can not be excluded.
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.
Today's volumes of traffic require more and more responsibility from each individual road user in their interactions. Those who drive motor vehicles have the singular obligation to minimise the risk of accidents and hence the severity of injuries, particularly with a view to the most vulnerable road users such as motor bikes, bikes and pedestrians. Since responsible and pro-active driving depends first and foremost on the visual information relayed by our eyes and the visual channel this requires good command of the traffic and all-round visibility from our driver's seat. Granted that human error can never be fully excluded, improving visibility around the car is nevertheless an urgent priority. To do so, we need to rate visibility in the most realistic driving situations. Since the existing visibility metrics and methodology are not applicable to real-life driving situations, this study aimed at developing a new visibility rating methodology based on real-life accident scenarios. On the basis of the cases documented by the accident research project, this study analysed criteria indicative of diminishing visibility on the one hand and revealing some peculiarities in connection with the visibility issue on the other. Based on the above, the project set out to develop a rating methodology allowing to assess all-round visibility in various road situations taking into account both driver and road geometries. In this context, the assessment of visibility while turning a corner, crossing an intersection and joining traffic on a major road (priority through route) is of major importance. The first tests have shown that critical situations can be avoided by adapting the relevant geometries and technical solutions and that significant improvements of road safety can be derived therefrom.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
The project UR:BAN "Cognitive assistance (KA)" aims at developing future assistance systems providing improved performance in complex city traffic. New state-of-the-art panoramic sensor technologies now allow comprehensive monitoring and evaluation of the vehicle environment. In order to improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is the evaluation and prediction of their behaviour and actions. The objective of subproject "WER" is development support by providing quantitative estimates of traffic collisions at the very start and predict potential in terms of optimized accident avoidance and reduction of injury severity. For this purpose an integrated computer simulation toolkit is being devised based on real world accidents (GIDAS as well as video documented accidents), allowing the prediction of potential effectiveness and future benefit of assistance systems in this accident scenario. Subsequently, this toolkit may be used for optimizing the design of implemented assistance systems for improved effectiveness.
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.
India is one of the leading countries reporting highest road accidents & related injuries. TMARG (Tata Motors Accident Research Group) has been recording crashes in association with M/s. Lokamanya Medical Foundation since 2011 with M/s, Amandeep Hospitals since Aug 2013. This study has highlighted some accident types not discussed extensively in literature. Trucks to Truck impacts " Cabin interaction with overhanging loadbody structures and Offset underside impacts for passenger vehicles are seen in significant numbers. The paper discusses these in more detail including severity.
Within the COST Action TU1101 the working group WG 1 is dealing with acceptance criteria and problems in helmet use while bicycling concerning conspicuity, thermal stress, ventilation deficits and other potential confounding. To analyze the helmet usage practice of bicyclists in Europe a questionnaire was developed in the scope of working group 1 to collect relevant information by means of a field study. The questionnaire consists of some 66 questions covering the fields of personal data of the cyclist, riding und helmet usage habits, information concerning the helmet model and the sensation of the helmet, as well as information on previous bicycle accidents. A second complementary study is conducted to analyze if the use of a bicycle helmet influences the seating geometry and the posture of cyclists when riding a bicycle and if the if the helmet vertically limits the vision. For this purpose cyclists with and without helmets were photographed in real world situations and relevant geometrical values such as the decline of the torso, the head posture of the upper vertical vision limit due to the helmet were established from the photos. The interim results of the field studies which were conducted in Germany by the Hannover Medical School are presented in this study. Some 227 questionnaires were filled out, of which 67 participants had used a helmet and 42 of the 227 participants have had a bicycle accident before. For the analysis of the riding position and posture of the cyclist over 40 pictures of riders with a helmet and over 240 pictures of riders without a helmet were measured concerning the seating geometry to describe the influence of using a bicycle helmet. Some results in summary: From the riders interviewed with the questionnaire only 11% of the city bike riders and 12% of the mountain bike riders always used the helmet, while 38% of the racing bike riders and 88% of the e-bike-riders always used the helmet. The helmet use seems not to change the sensation of safety of cycling compared to the use of a car. The arguments for not wearing a helmet are mostly stated to be the short distance of a trip, high temperatures or carelessness and waste of time. The reasons for using a helmet are stated to be the feeling of safety and being used to using a helmet. Being a role model for others was also stated to be a reason for helmet use. Concerning the sensation of the helmet 9% of the riders reported problems with the field of vision when using a helmet, 57% saw the problem of sweating too much, and 10% reported headaches or other unpleasant symptoms like pressure on the forehead when using the helmet. The analysis of the seating posture from the pictures taken of cyclists revealed that older cyclists generally have a riding position where the handle bar is higher than the seat (0-° to 10-° incline from seat to handlebar), while younger riders had a higher variance (between -10-° decline and 20-° incline). Further, elderly riders and riders with helmets seem to have a more upright position of the upper body when cycling. The vertical vision limit due to the helmet is determined by the front rim of the helmet (mostly the sun shade). Typical values here range from 0-° (horizontal line from the eye to the sun shade) to 75-° upwards, in which elderly riders tend to have a slightly higher vertical vision limit possibly due to the helmet being worn more towards the face.