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The second ESAR Conference took place at the Medical University Hannover. This year conference presents the current state of affairs of relevant research activities in the field of in-depth investigations. The first conference on ESAR (Expert Symposium on Accident Research) was established in 2004. It is planned to hold ESAR every two years. Hannover seems to be the right place for this conference concerning the fact that the first in-depth research team was found here in the year 1973 and comprehensive studies on accident analysis were spread out from here around the world continuously. This year conference topped all expectations in terms of the numbers of participants, in the variety of papers and the interdisciplinary of presenters from medical, psychological and engineering background. More than 100 delegates from all over the world, that means 13 different countries and from 4 different continents, came to Hannover, presented their results of accident investigation and discussed countermeasures for accident prevention and injury reduction. ESAR should be a platform for exchange of knowledge to find an optimized way for increase of traffic and vehicle safety by in-depth investigation and methodology. ESAR as international conference should be a platform for consideration of all nations round the world. This seems to be very important for the current situation, having high safety in the high industrial countries of Europe, US and Australia, but low safety and high injury risk in Asia and Africa.
Im September 2005 wurde erstmals eine FERSI Scientific Road Safety Research Conference durchgeführt. Mit der Konferenz sollten Resultate und Bearbeitungsstände der gemeinsamen europäischen Forschungsprojekte der FERSI Mitglieder präsentiert werden. Darüber hinaus sollten die Ergebnisse wichtiger nationaler Forschungsprojekte eingebunden sowie den Projektbearbeitern Gelegenheit zum internationalen "Networking" gegeben werden. Wolfgang Hahn, Leiter der Abteilung Straßenbau und Straßenverkehr beim Bundesministerium für Verkehr-, Bau- und Wohnungswesen unterstrich in seiner Eröffnungsrede die Notwendigkeit einer in Europa koordinierten Verkehrssicherheitsforschung, um gemeinsam zu einer Verbesserung der Straßenverkehrssicherheit zu gelangen. Aus Sicht des Leiters des Referates "Sicherheit im Straßenverkehr" der DG TREN, Dimitrios Theologitis, besteht die zentrale Aufgabe der zukünftigen europäischen Verkehrssicherheitsforschung in der Entwicklung und Verbreitung von "Best Practices". Auch er betonte, dass die Verkehrssicherheitsprobleme in Europa auch in Zukunft nur durch eine enge Zusammenarbeit der EU-Mitgliedsländer im Bereich der Forschung und durch die Umsetzung der dabei erzielten Forschungsergebnisse zu lösen seien.rnIm Anschluss an die Eröffnungsreden stellten Rune Elvik, TOI (Norwegen), Marc Gaudry, INRETS (Frankreich), David Lynam, TRL (United Kingdom) und Dr. Rudolf Krupp, BASt (Germany), in ihren Vorträgen herausragende Forschungsergebnisse im Bereich der Straßenverkehrssicherheit vor. Die sich an diese erste Vortragsrunde anschließenden Workshops waren entsprechend der Themenschwerpunkte "Daten, Strategien und Kommunikation", "Verhalten und Aufklärung" sowie "Technische Anwendungsmöglichkeiten" unterteilt. Jeder Themenschwerpunkt wurde durch 4 nacheinanderfolgende Workshops abgedeckt. In einer abschließenden Sitzung wurden die wichtigsten Ergebnisse der einzelnen Workshops vom jeweiligen Chairman des Workshops dem gesamten Plenum vorgestellt. rn
Validation of human pedestrian models using laboratory data as well as accident reconstruction
(2007)
Human pedestrian models have been developed and improved continually. This paper shows the latest stage in development and validation of the multibody pedestrian model released with MADYMO. The biofidelity of the multibody pedestrian model has been verified using a range of full pedestrian-vehicle impact tests with a large range in body sizes (16 male, 2 female, standing height 160-192cm, weight 53.5-90kg). The simulation results were objectively correlated to experimental data. Overall, the model predicted the measured response well. In particular the head impact locations were accurately predicted, indicated by global correlation scores over 90%. The correlation score for the bumper forces and accelerations of various body parts was lower (47-64%), which was largely attributed to the limited information available on the vehicle contact characteristics (stiffness, damping, deformation). Also, the effects of the large range in published leg fracture tolerances on the predicted risk to leg fracture by the pedestrian model were evaluated and compared with experimental results. The validated mid-size male model was scaled to a range of body sizes, including children and a female. Typical applications for the pedestrian models are trend studies to evaluate vehicle front ends and accident reconstructions. Results obtained in several studies show that the pedestrian models match pedestrian throw distances and impact locations observed in real accidents. Larger sets of well documented cases can be used to further validate the models especially for specific populations as for instance children. In addition, these cases will be needed to evaluate the injury predictive capability of human models. Ongoing developments include a so-called facet pedestrian model with a more accurate geometry description and a more humanlike spine and neck and a full FE model allowing more detailed injury analysis.
Internationally, the need is expressed for harmonized traffic accident data collection (PSN, PENDANT, etc.). Together with this effort of harmonization, traffic accident investigation moves more and more in the direction of accident causation. As current methods only partly address these needs, a new method was set up. The main characteristics of this method are: • Accident/injury causation (associated) factors can objectively be identified and quantified, by comparison with exposure information from a normal population. • All relevant accident and exposure data can be included: human-, vehicle-, and environmental related data for the pre-crash, crash and postcrash situation (the so-called Haddon matrix). The level of detail can be chosen depending on interest and/or budget, which makes the method very flexible. In this paper the accident collection and control group method are presented, including some of the achieved results from a pilot study on 30 truck accidents and 30 control locations. The data were analyzed by using cross-tabulations and classification-tree analysis. The method proved useful for the identification of statistically significant causational aspects.
Since 2005 the German In-Depth Accident Study (GIDAS) also records aspects of active vehicle safety. This is done because vehicles are fitted with an increasing number of active safety devices which have undoubtedly an influence on the number, severity and course of accidents. Accident researchers expect that collecting active safety data will facilitate to assess and quantify the impact of these and future devices. It is the aim of this paper to outline benefits and limitations associated with the recording of active safety aspects within indepth studies. An overview about possible areas where active safety data can be useful will be given. For that purpose single safety or comfort systems will be selected to estimate the effects of an accident database which includes variables associated with these systems. Questions with regard to the limitations of collecting active safety data will be addressed. Possible items are for example the usability of the data recorded, the real accident cause, the small number of relevant accidents, the time span needed to gather a sufficient dataset, the small share of vehicles equipped with a certain system or different functionalities of systems that are supposed to fall in the same category. As a result user needs for a reasonable data collection of active safety elements will be elaborated.
Description of road traffic related knee injuries in published investigations is very heterogeneous. The purpose of this study was to estimate the risk of knee injuries in real world car impacts in Germany focusing vulnerable road users (pedestrians, bicyclists and motorcyclists) and restrained car drivers. The accident research unit analyses technical and medical data collected shortly after the accident at scene. Two different periods (years 1985-1993 and 1995-2003) were compared focusing on knee injuries (Abbreviated Injury Scale (AISKnee) 2/3). In order to determine the influences type of collision, direction and speed as well as the injury pattern and different injury scores (AIS, MAIS, ISS) were examined. 1.794 pedestrians, 742 motorcyclists, 2.728 bicyclists and 1.116 car drivers were extracted. 2% had serious ligamentous or bony injuries in relation to all injured. The risk of injury is higher for twowheelers than for pedestrians, but knee injury severity is higher for the latter group. Overall the current knee injury risk is low and significant reduced comparing both time periods (27%, p<0,0001). Severe injuries (AISKnee 2/3) were below 1%). Improved aerodynamic design of car fronts reduced the risk for severe knee injuries significantly (p=0,0015). Highest risk of injury is for motorcycle followed by pedestrians, respectively. Knee protectors could prevent injuries by reducing local forces. The classically described dashboard injury was rarely identified. The overall injury risk for knee injuries in road traffic is lower than estimated and reduced comparing both periods. The aerodynamic shape of current cars compared to older types reduced the incidence and severity of knee injuries. Further modification and optimization of the interior and exterior design could be a proper measurement. Classic described injury mechanisms were rarely identified. It seems that the AIS is still underestimating extremity injuries and their long term results.
The accident research project in Dresden was founded in July 1999. To date over 6.000 crash investigations have been undertaken. About 10.000 vehicles have been documented and over 13.000 participants have been debriefed. But there is much more than this scientific success. Because of the interdisciplinary character between the medical and technical focus, the project affords an important contribution for the education of the involved students. Over 200 students of different fields of study have got experiences not only for the occupational career. This lecture describes the additional effects of the accident research project regarding the education of the students, the capacity for teamwork and learning about dealing with accident casualties.
Empirical vehicle crashworthiness studies are usually based on national or in-depth traffic accident surveys: Data on accident-involved cars/drivers are analysed in order to quantify the chance of driver injury and to assess certain risk factors like car make and model. As the cars/drivers involved in the same accident form a "cluster", where the size of the cluster equals the number of accident-involved parties, traffic accident survey data are typical multi-level data with accidents as first-level or primary and cars/drivers as secondlevel or secondary units (car occupants in general are to be considered as third level units). Consequently, appropriate statistical multi-level models are to be used for driver injury risk estimation purposes as these models properly account for the cluster structure of traffic accident survey data. In recent years various types of regression models for clustered data have been developed in the statistical sciences. This paper presents multi-level statistical models, which are generally applicable for vehicle crashworthiness assessment in the sense that data on single and multiple car crashes can be analysed simultaneously. As a special case of multi-level modelling driver injury risk estimation based on paired-by-collision car/driver data is considered. It is demonstrated that assessment results may be seriously biased, if the cluster structure inherent in traffic accident survey data is erroneously ignored in the data analysis stage.
There is a need for detecting characteristics of pedestrian movement before car-pedestrian collisions to trigger a fully reversible pedestrian protection system. For this purpose, a pedestrian sensor system has been developed. In order to evaluate the effectiveness of the sensor system, the in-depth knowledge of car-pedestrian impact scenarios is needed. This study aims at the evaluation of the sensor system. The accident data are selected from the STRADA database. The accident scenarios available in this database were evaluated and the knowledge of the most common scenarios was developed in terms of the pedestrian trajectory, the pedestrian speed, the car trajectory, the car velocity, etc. A mathematical model was then established to evaluate the sensor system with different detective angles. It was found that in order to detect all the pedestrians in the most common scenarios on time the sensor detective angle must be kept larger than 60 degrees.
The fact that ADAC Air Rescue handles approximately 4,000 road accident missions every year gave rise to set up an accident research programme for which ADAC Air Rescue provides its data. This data is of initial informational quality and will be supplemented by data from the police, experts, fire brigades as well as hospitals and forensic institutes. Although the number of cases is still rather low, certain tendencies can be identified. The causes for most accidents occur when joining or intersecting traffic, followed by speeding in road bends and tailgating. Many accidents involve HGV rear end collisions, often causing serious injuries, considerable damage and technical problems for the rescue operations. With regard to the various impact types, it has become obvious that most of the extremely serious injuries are inflicted during a passenger car side impact. In addition, access to and removal of trapped passengers is becoming more and more complicated, partly due to the increasing use of high-strength materials, and rescue operations tend to be more time consuming.