Sonstige
Verkehrspsychologische Nachschulungen stellen Maßnahmen zur Rehabilitierung von im Straßenverkehr auffälligen Kraftfahrerlnnen dar. Diese gesetzlich verankerten psychologischen lnterventionsprogramme werden mit hohem Aufwand konzipiert und sind bei der täglichen Durchführung mit beträchtlichen Kosten verbunden. Daraus ergibt sich die Notwendigkeit, die Effektivität der Nachschulungsmodelle durch eine wissenschaftliche Evaluation zu klären. Um die Effektivität der Nachschulungskurse der AAP (Austrian Applied Psychology) zu überprüfen wurde eine Fragebogenstudie mit Pre-Posttest-Designs durchgeführt. Die Ergebnisse der Alkoholkurse zeigen positive Auswirkungen hinsichtlich Einstellungsänderung, spezifischer Selbstwirksamkeitserwartung, interner Attributionen, Wissen und Gesamtbeurteilung.
Im Jahr 2005 wurde mit dem Bau der Niederrheinbrücke Wesel der Bau der Ortsumgehung Wesel begonnen. Der Beitrag berichtet über einige Ausführungsdetails der im Jahr 2009 fertiggestellten Baumaßnahme: die Herstellung des Pylons in hochfestem Beton, die Montage der Strombrücke, der Einsatz von Parallellitzenbündeln.
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 main objective of EC CASPER research project is to reduce fatalities and injuries of children travelling in cars. Accidents involving children were investigated, modelling of human being and tools for dummies were advanced, a survey for the diagnosis of child safety was carried out and demands and applications were analysed. From the many research tasks of the CASPER project, the intention of this paper is to address the following: • In-depth investigation of accidents and accident reconstruction. These will provide important points for the injury risk curve, in order to improve it. Different accident investigation teams collected data from real road accidents, involving child car passengers, in five different European countries. Then, a selection of the most appropriate cases for the injury risk curve and the purposes of the project was made for an in-depth analysis. The final stage of this analysis was to conduct an accident reconstruction to validate the results obtained. The in-depth analysis included on-scene accident investigation, creating virtual simulations of the accident/possible reconstruction, and conducting the reconstruction. In the cases of successful reconstructions, new points were introduced to the injury risk curves. Accident reconstructions of selected cases were carried out in test laboratories as the next step following in-depth road accident investigation. These cases were reconstructed using similar child restraint systems (CRS) and the same type make and model as in the real accidents. Reconstructing real cases has several limitations, such as crash angle, cars" approximation paths and crash speed. However, a few changes and applications on the testing conditions were applied to reduce the limitations and improved the representations of the real accidents. After conducting the reconstructions, a comparison between the deformations of the cars on the real accident and the vehicles from the reconstructions was made. Additionally, a correlation between the data captured from the dummies and the injury data from the real accident was sought. This finalises an in-depth analysis of the accident, which will provide new relevant points to the injury risk curve. The CASPER project conducted a large research programme on child safety. On technical points, a promising research area is the developing injury risk curves as a result of in-depth accident investigations and reconstructions. This abstract was written whilst the project was not yet finished and final results are not yet known, but they will be available by the time of the conference. All the works and findings will not necessarily be integrated in the industrial versions of evaluation tools as the CASPER project is a research program.
Causation patterns and data collection blind spots for fatal intersection accidents in Norway
(2010)
Norwegian fatal intersection accidents from the years 2005-2007 were analysed to identify any causation patterns among their underlying contributing factors, and also to evaluate whether the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to perform causation pattern analysis. A total of 28 fatal accidents were analysed. Details on crash contributing factors for each driver in each crash were first coded using the Driving Reliability and Error Analysis Method (DREAM), and then aggregated based on whether the driver was going straight or turning. Analysis results indicate that turning drivers to a large extent are faced with perception difficulties and unexpected behaviour from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers going straight on the other hand have less perception difficulties. Instead, their main problem is that they largely expect turning drivers to yield. When this assumption is violated, they are either slow to react or do not react at all. Contributing factors often pointed to in literature, e.g. high speed, drugs and/or alcohol and inadequate driver training, played a role in 12 of 28 accidents. While this confirms their prevalence, it also indicates that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, information on blunt end factors (those more distant in time/space, yet important for the development of events) was more limited than information on sharp end factors (those close in time/space to the crash). A possible explanation is that analysts may view some blunt end factors as event circumstances rather than contributing factors in themselves, and therefore do not report them. There was also an asymmetry in terms of reported obstructions to view due to signposts and vegetation. While frequently reported as contributing for turning drivers, they were rarely reported as contributing for their counterparts in the same accidents. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver legally held liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator mindset needs addressing to avoid future bias in crash investigation reports.
Accident data shows that the vast majority of pedestrian accidents involve a passenger car. A refined method for estimating the potential effectiveness of a technology designed to support the car driver in mitigating or avoiding pedestrian accidents is presented. The basis of the benefit prediction method consists of accident scenario information for pedestrian-passenger car accidents from GIDAS, including vehicle and pedestrian velocities. These real world pedestrian accidents were first reconstructed and the system effectiveness was determined by comparing injury outcome with and without the functionality enabled for each accident. The predictions from Volvo Cars" general Benefit Estimation Model are refined by including the actual system algorithm and sensing models for a relevant car in the simulation environment. The feasibility of the method is proven by a case study on a authentic technology; the Auto Brake functionality in Collision Warning with Full Auto Brake and Pedestrian Detection (CWAB-PD). Assuming the system is adopted by all vehicles, the Case Study indicates a 24% reduction in pedestrian fatalities for crashes where the pedestrians were struck by the front of a passenger car.
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.
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.
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.
Analysis of the accident scenario of powered two-wheelers on the basis of real-world accidents
(2013)
For the first time since 20 years the German national statistics of traffic accidents revealed an increasing number of fatalities and seriously injured persons in 2011. This negative development was especially caused by increasing numbers in all groups of vulnerable road users (VRU). Furthermore, the comparison of fatality reduction rates between several categories of road users shows that persons on motorcycles show the worst performance over years. Although every second fatality in German traffic accidents is still a car occupant, users of PTW make up more than 20% in the meantime. Assuming further improvements in the field of occupant protection this trend will continue. For that reason, a study on the basis of real-world accidents was conducted to describe the accident scenario involving motorcycles and to identify the reasons of the above-described fact. Approximately 1.800 motorcycle accidents out of GIDAS database were used for the analyses. The first part of the study deals with the question how representative the GIDAS database is for the German motorcycle accident scenario. Afterwards, detailed descriptive statistics on motorcycle accidents were presented considering numerous parameters about the accident scene, environmental influences, vehicle information, individual characteristics, interview data, injury severity and injury causation. One important point is the identification of the most frequent critical situations that are typical for motorcycle accidents. Furthermore, a special focus was on accident causation. Finally, conspicuous facts out of the analysis are emphasized. All in all, the study gives a comprehensive overview about the German motorcycle accident scenario. One the one hand, the use of weighted GIDAS data allows representative and robust statements on the basis of large case numbers; on the other hand highly detailed conclusions can be drawn. The results of the study help to understand the particularities of motorcycle accidents and provide approaches for further improvements in the field of PTW safety.