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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.
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.
Cycling supports the independence and health of the aging population. However, elderly cyclists have an increased injury risk. The majority of injured cyclists is victim of a single-sided accident, an accident in which there is no other party involved. The aim of the project "Safe and Aware on the bicycle" is to develop guidelines for an advisory system that is useful in preventing single-sided accidents. This system is able to support the elderly cyclist; enabling the cyclist to timely adapt his cycling behaviour and improve cycling safety and comfort. For the development of such advisory system the causes of singles accidents and the wishes of the elderly cyclist must be known. First step to obtain this insight was a literature survey and an GIDAS research. Unfortunately accidentology research with GIDAS did not give the full understanding of the pre-crash situations and (especially the behaviour related) factors leading to the accident. The second step was consultation of elderly cyclist through a questionnaire (n=800), in-depth interviews (n=12) and focus group sessions (n=15). This offered complementary information and a much better understanding of the behavioural aspects. Results concern the behaviour in traffic and identify specific physical (i.e. problems looking backwards over the shoulder) and mental issues. Furthermore, the needs and wishes for support in specific cycling situations were identified. In conclusion; The GIDAS results together with the information obtained contacting the elderly cyclists enabled setting up requirements for an advisory system, which is useful in preventing single-sided accidents.
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.
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.
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 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.
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.
This study aimed at developing an injury estimation algorithm for AACN technologies for Germany and compared them to findings based on Japanese data. The data to build and to verify the algorithm was obtained from the German in-depth Accident Database (GIDAS) and split into a training and a validation dataset. Significant input variables and the generalized linear regression model to predict severe injuries (ISS>15) were selected to maximize area under the receiver operating characteristic curve (AUC). Probit regression with the input parameter multiple impact, delta v, seatbelt use and impact direction gave the largest AUC of 0.91. Sensitivity of the algorithm was validated at 90% and specificity at 76% for an injury risk threshold of 2%. It appears that no major differences between Japan and Germany exist for injury estimation based on delta v and impact direction. However, far side impact and multiple crash events appear to be associated with a larger risk increase in the German data.
The study aimed at estimating the impact of pedelecs (with an assumed higher speed than bicycles) on the traffic accident severity in Germany for different penetration rates. The analysis shows that in many real situations (68%) an electrical support of bicycles has no influence on the sequence of accident events. Taking into account a number of unreported "single bicycle accidents", the adoption of similar traffic behavior and similar age distribution, the authors determined a shift of 400 former slightly to seriously injured cyclists in Germany per year. Overall this would be an increase of approximately 2.3% in case of 10% of pedelec penetration with the pessimistic assumption of 10 km/h speed increase although first natural driving studies predict a much lower average speed increase of pedelecs. The hypothesis verbalized in the initial question whether a higher distribution of pedelecs will result in more severe accidents in Germany is not verified. The study shows that electrical support didn"t result in higher collision speed in general. In many accident situations, the speed of pedelecs has only a minor influence on the accident severity. Further research focusing on a possible change of driver behavior especially in new target groups (elderly people) will be needed.
Event data recorders (EDRs) are a valuable tool for in-depth investigation of traffic accidents. EDRs are installed on the airbag control module (ACM) to record vehicle and occupant information before, during, and after a crash event. This study evaluates EDR characteristics and aims at better understanding EDR performance for the improvement of accident reconstruction with more reliable and accurate information regarding accidents. The analysis is based on six crash tests with corresponding EDR datasets.
The current paper reports on the results of a pilot study aiming to investigate the effect of mobile telephone use on the driving performance of 5 amateur and 5 professional drivers. Their driving acuity was tested through a driving simulator. Analysis and interpretation of the results occurred comparing the drivers' driving performance while talking, reading messages and writing a message on the mobile phone (intervention time) with the drivers' driving performance engaged in no activity (control time). The variables affected by the mobile phone were the "steering", the "lane offset" and the "duration of lane offset". Moreover, the drivers involved in a car crash in the last five years appeared to differ from those who were not involved in a crash in both "lane offset" and "following distance". The results of this pilot study will inform the design of a large experimental study on 50 professional and 50 amateur drivers.
Road accidents are typically analyzed to address influences of human, vehicle, and environmental (primarily infrastructure) factors. A new methodology, based on a "Venn diagram" analysis, gives a broader perspective on the probable factors, and combinations of factors, contributing both to the occurrence of a crash and to sustaining injuries in that crash. The methodology was applied to 214 accidents on the Mumbai-Pune expressway. Factors contributing to accidents and injuries were addressed. The major human factors influencing accidents on this roadway were speeding (30%) and falling asleep (29%), while injuries were primarily due to lack of seat belt use (46%). The leading infrastructure factor for injuries was impact with a roadside manmade structure (28%), and the main vehicle factor for injuries was passenger compartment intrusion (73%). This methodology can help identify effective vehicle and infrastructure-related solutions for preventing accidents and mitigating injuries in India.
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.
Introduction: The method of causation analysis applied under the German accident survey GIDAS, which is based on Accident Causation Analysis System (ACAS) focuses on an on-scene data collection of predominantly directly event-related causation factors which were crucial in the accident emergence as situational resulting events and influences. The paradigm underlying this method refers to the findings of the psychological traffic accident research that most causally relevant features of the system components human, infrastructure and vehicle technology are found directly in the situation shortly before the accident. This justifies the survey method which is conducted directly at the accident (on-scene), shortly after the accident occurrence (in-time) with the detection of human-related causes (in-depth). Human aspects of the situation analysis that interact and influence the risk situations shortly before the collision are reported as errors, lapses, mistakes and failures in ACAS in specific categories and subcategories. Thus methodically ACAS is designed primarily for the collection of accident features on the level of operational action, which certainly leads to valid findings and behavioral causes of accidents. The enhancement by means of Moderating Conditions concerns the pre-crash phase in different levels: strategical, tactical and operational.
SEEKING is looking for answers regarding electric powered bicycles and their relation to traffic safety issues. Does a cyclist need "E"? Is it as risky as riding a moped or are E-bikes creating conflicts with other cyclists? The project described herein, funded by the Austrian Ministry of Transport, has the aim of seeking answers to these hot topics. The SEEKING-team shows an in-depth investigation of vehicle dynamic sensing, together with subjective feedback of test riders to detect similarities and differences between conventional cycling and E-biking. Following an overview on the international status quo, measurement runs and their analyses are performed to find a set of preventative measures to make (E-)biking safer. A specific focus is the detection of curve handling, stopping and acceleration phases as well as conflict studies on course-based test rides and "real world" tests on cycling paths (naturalistic riding).
Within the overall system of novice driver preparation, the practical driving test plays an especially important role for the objective of improved driving safety: On the one hand, the test contents, assessment criteria and test results provide important orientation for the organisation of driving school training and the individual learning processes of the novice drivers (control function); on the other hand, the practical test serves to ensure that only novice drivers with adequate driving competence are entitled to participate in motorised road traffic (selection function). The aim of the present project is to elaborate a scientifically founded model for a future, optimised practical driving test, together with a contextual and methodical (implementation) concept for its continuous maintenance, quality assurance and further development. In addition, the institutional structures of the test system, test methods and test procedures - including the necessary demand, assessment, documentation and evaluation standards - are to be described in a "System Manual on Driver Licensing (Practical Test)". As a first step, selected psychology-based driving competence models and the contents of training and test documents are to be analysed. The results of this analysis will then serve as the starting point for a discussion of possibilities to model and measure driving competence, and for the outlining of a driving competence model for the theoretical determination of appropriate test content. Subsequently, demand standards for an optimised practical driving test can be derived by applying action theory principles to the demands of motor vehicle handling, and thereby defined as minimum personal standards for driving test candidates. This elaboration is to take into account not only latest knowledge from the fields of traffic and test psychology, but also relevant stipulations in licensing regulations, international trends in the further development of test standards, and novice-specific accident causes and competence deficits. A further outcome of the project - alongside theoretical-methodical foundations for optimisation of the practical driving test and for the draft of a system manual - is to be a "Catalogue of driving tasks (Category B)", in which the demand standards for the practical driving test are described in the form of situation-related driving tasks and situation-independent observation categories, as a means to specify the criteria for event-oriented performance assessment and overall competence evaluation. At the same time, criteria for the examiner's test decision are to be defined. This optimisation work will contribute, finally, to further development of the adaptive control strategy for the practical driving test. To enable implementation of the further developed demand, assessment and documentation standards of an optimised practical driving test, a contextual and methodical concept for an electronic test report is to be presented, together with an ergonomically founded design proposal for both hardware and software. The computer-assisted documentation of test performance is intended to support the driving test examiner in planning of the course of a driving test and assessment of the candidate's driving behaviour. Furthermore, optimisation of the performance feedback to candidates and improved possibilities for scientific evaluation of the optimised practical driving test are expected. With regard to test evaluation, a fundamental model is to be described, which - alongside monitoring of the psychometric quality criteria within the framework of an instrumental evaluation - incorporates an evaluation of test results, product audits and the responses to candidate and driving instructor surveys. Finally, the possible influence of driver assistance and accident avoidance systems on the realisation of a driving test and on the assessment of test performance is to be discussed.
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.
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).
This study aimed at prediction of long bone fractures and assessment of lower extremity injury mechanisms in real world passenger car to pedestrian collision. For this purpose, two pedestrian accident cases with detail recorded lower limb injuries were reconstructed via combining MBS (Multi-body system) and FE (Finite element) methods. The code of PC Crash was used to determine the boundary conditions before collision, and then MBS models were used to reproduce the pedestrian kinematics and injuries during crash. Furthermore, a validated lower limb FE model was chosen to conduct reconstruction of injuries and prediction of long bone fracture via physical parameters of von Mises stress and bending moment. The injury outcomes from simulations were compared with hospital recorded injury data and the same long bone fracture patterns and positions can be observed. Moreover, the calculated long bone fracture tolerance corresponded to the outcome from cadaver tests. The result shows that FE model is capable to reproduce the dynamic injury process and is an effective tool to predict the risk of long bone fractures.