Sonstige
Filtern
Erscheinungsjahr
Dokumenttyp
Schlagworte
- Data acquisition (56) (entfernen)
Institut
- Sonstige (56) (entfernen)
Impact severity is a fundamental measure for all in-depth crash investigation projects. One methodology used in the UK is based on the US Calspan software package CRASH3. The UK- in-depth crash investigation studies routinely use AiDamage3 a software package which is based on an updated version of the original CRASH3 algorithm, including enhancements to the vehicle stiffness coefficients. Real world accident-damaged vehicles are measured and their crush is correlated with a library of stiffness coefficients. These measurements are then used, along with other parameters, to calculate the crash energy and equivalent changes of velocity of the vehicles (delta-v), which is a measure of the impact severity. UK in-depth accident studies routinely validate the crash severity methodologies applied as the vehicle fleet changes. This is achieved by analysing crash test data and using the appropriate residual crush damage and other inputs to AiDamage3 and checking the program- outputs with the known crash severity parameters. This procedure checks, at least in part, the default stiffness values in the data libraries and the reconstruction methods used.
Each year the traffic accident research teams in Dresden and Hanover provide an in-depth investigation of approximately two thousand accidents, aggregated in the GIDAS database. To accomplish a comprehensive review of each traffic accident recorded, a sensible and thorough encoding of suffered injuries is indispensable. The Abbreviated Injury Scale by AAAM offers a valuable and handy solution to achieve this goal. However, there were a few difficulties in the use of the AIS that came up in the past, which let to necessary improvements for the utilization of the AIS 2005 for GIDAS.
Nowadays, traffic accidents are recorded in historical databases. Regarding the huge quantity of data, the use of data mining tools is essential to help Experts, for automatically extracting relevant information in order to establish and quantify relations between severity and potential factors of accidents. An innovative approach is here proposed for an in depth investigation of real world accidents data base. Mutual information ratio based on conditional entropies is used to quantity the association strength between an accident outcome descriptor (injury severity) and other potential association factors. Information theoretic methods help to select automatically groups of factors mostly responsible of the severity of accident.
In the context of the COST357 research project, the climatic conditions and requirements for protective helmets for motorcyclists have been examined. The extent to which these factors would influence motorbike handling and accidents in which motorcyclists are involved have also been examined. This project addresses how cognitive abilities of motorcyclists relate to helmet construction factors. In particular, the aspects of motorcycle driver helmets are to be parameterized in order that they may be used subsequently as a basis for future requirement profiles. The task of one working group of the COST357 project has been to analyse accident events and to identify helmet design issues which affect motorcycle drivers while wearing a helmet. This has been achieved by collating accident data across different countries recorded in the course of in-depth investigations at the site of accidents and by combining this with field studies of motorcyclists participating in traffic, but not involved in accidents. This paper presents the study methodology, database and first results of this international survey. The basis of the study has been a total of 424 interviews of motorcyclists and 134 motorcycle accidents, which were collected across Germany, Greece, Italy, Ireland, Portugal and Turkey and combined in a single database.
A lack of representative European accident data to aid the development of safety policy, regulation and technological advancement is a major obstacle in the European Union. Data are needed to assess the performance of road and vehicle safety and is also needed to support the development of further actions by stakeholders. This short-paper describes the process of developing a data collection and analysis system designed to partly fill these gaps. A project team with members from 7 countries was set up to devise appropriate variable lists to collect fatal crash data under the following topic levels: accident, road environment, vehicle, and road user, using retrospective detailed police reports (n=1,300). The typical level of detail recorded was a minimum of 150 variables for each accident. The project will enable multidisciplinary information on the circumstances of fatal crashes to be interpreted to provide information on a range of causal factors and events surrounding the collisions.
The SafetyNet project was formulated in part to address the need for safety oriented European road accident data. One of the main tasks included within the project was the development of a methodology for better understanding of accident causation together with the development of an associated database involving data obtained from on-scene or "nearly onscene" accident investigations. Information from these investigations was complemented by data from follow-up interviews with crash participants to determine critical events and contributory factors to the accident occurrence. A method for classification of accident contributing factors, known as DREAM 3.0, was developed and tested in conjunction with the SafetyNet activities. Collection of data and case analysis for some 1 000 individual crashes have recently been completed and inserted into the database and therefore aggregation analyses of the data are now being undertaken. This paper describes the methodology development, an overview of the database and the initial aggregation analyses.
As the official German catalogue of accident causes has difficulty in matching the increasing demands for detailed psychologically relevant accident causation information, a new system, based on a "7 Steps" model, so called ACASS, for analyzing and collecting causation factors of traffic accidents, was implemented in GIDAS in the year 2008. A hierarchical system was developed, which describes the human causation factors in a chronological sequence (from the perception to concrete action errors), considering the logical sequence of basic human functions when reacting to a request for reaction. With the help of this system the human errors of accident participants can be adequately described, as the causes of each range of basic human functions may be divided into their characteristics (influence criteria) and further into specific indicators of these characteristics (e.g. distraction from inside the vehicle as a characteristic of an observation-error and the operation of devices as an indication for distraction from inside the vehicle. The causation factors accordingly classified can be recorded in an economic way as a number is assigned to each basic function, to each characteristic of that basic function and to each indicator of that characteristic. Thus each causation factor can be explicitly described by means of a code of numbers. In a similar way the causation factors based on the technology of the vehicle and the driving environment, which are also subdivided in an equally hierarchical system, can be tagged with a code. Since the causes of traffic accidents can consist of a variety of factors from different ranges and categories, it is possible to tag each accident participant with several causation factors. This also opens the possibility to not only assign causation factors to the accident causer in the sense of the law, but also to other participants involved in the accident, who may have contributed to the development of the accident. The hierarchical layout of the system and the collection of the causation factors with numerical codes allow for the possibility to code information on accident causes even if the causation factor is not known to its full extent or in full detail, given the possibility to code only those cause factors, which are known. Derived from the systematic of the analysis of human accident causes ("7 steps") and from the practical experiences of on-scene interviews of accident participants, a system was set in place, which offers the possibility to extensively record not only human causation factors in a structured form. Furthermore, the analysis of the human causation factors in such a structured way provides a tool, especially for on-scene accident investigations, to conduct the interview of accident participants effectively and in a structured way.
While many medical studies have dealt with the incidence, nature and treatment of polytrauma the injury-causing accident mechanisms are rarely discussed in detail, mostly due to the lack of documentation of the technical aspects. The present prospective study was started in late 2007 and collects data from traffic accidents with most severely injured in six south- German counties and two larger cities for the duration of one year. It is aimed at identifying and documenting all polytrauma cases (ISS ≥ 16) caused by traffic accidents and their crash circumstances. The data collection is based on an interdisciplinary concept to include both the police, emergency dispatch centers, hospitals and fire departments in the region and is completely anonymous. Potentially relevant cases where an emergency physician was called to the scene of a traffic accident are provided by the dispatch center. All three hospitals in the region suited for the treatment of polytraumatised patients record injuries, major diagnostic and surgery data. Data and images from the accident scene are provided by the police and by fire departments. The latter provide information which is usually not available from the police, like deployed airbags, vehicle extrication measures and detailed views of car interiors. The main objective of the study is to determine the structure of road users who sustain a polytrauma, their crash opponents and the injury patterns found in relation to the collision configuration and the protection by seat belts, air bags and other devices. With detailed documentation of vehicle damage and extrication measures the study is also intended to support the development of injury predictors for pre-hospital treatment and provide field data regarding further improvement of technical rescue.
The Centre for Automotive Safety Research (formerly the Road Accident Research Unit) at the University of Adelaide in South Australia has a history of in-depth crash investigation going back to the 1970s. In recent years, our focus has been on studying factors that contribute to road crashes, with an emphasis on the role of road infrastructure. Our method involves crash notification by the South Australian Ambulance Service and detailed investigation of the crash scene usually before the crash-involved vehicles have been moved. This at-scene data collection is supplemented with police crash reports, Coroner- reports including autopsy findings for fatal crashes, case notes from hospitals for all injured persons, structured interviews with crash participants and witnesses, and computerised reconstruction of the events of the crash. One of the most notable research findings to emerge from our in-depth work has been the relationship between travelling speed and the risk of crash involvement. By comparing the calculated free speeds of crash-involved vehicles (cases) with the measured speeds of non-crash-involved vehicles travelling on the same roads at the same time of day (controls), we were able to establish that an exponential relationship exists between travelling speed and the likelihood of involvement in a casualty crash. This was the case for both metropolitan and rural areas. This research prompted the reduction of some speed limits in Australia, which has resulted in notable decreases in crash numbers. Another finding of interest in our recent investigation of 298 mostly daytime crashes in metropolitan Adelaide was that medical conditions make a sizeable contribution to the occurrence of road crashes. We found that almost half of the drivers, riders and pedestrians involved in the collisions had at least one pre-existing medical condition, and half of these individuals had two or more such conditions. We found that a medical condition was the direct causal factor in 13% of the casualty crashes investigated and accounted for 23% of all hospital admission or fatal crash outcomes. A follow-up study of all hospital admissions for road crashes in Adelaide is now going ahead to look further at this problem. The paper also describes studies looking specifically at pedestrian crashes. These include studies of the relationship between travelling speed and the risk of a fatal pedestrian crash, and studies utilising real crash data to validate headforms and test dummies used in the assessment of the safety of new vehicles in the event of a collision with a pedestrian.
Pedestrian accidents are one of the major concerns related with road accidents around the world. Portugal has one of the highest rates of pedestrian fatalities in Europe. In this paper an overview conditions were the pedestrian accidents occurred in Portugal is presented. In the last years, a project related with the pedestrian accidents has run in Portugal for the period 2004-2006 where 603 people died, 2097 have been severely injured and about 17000 slightly injured. Within this project all the pedestrian accidents in this period have been analysed providing global information about a wide range of aspects, since location, driver and pedestrian characteristics, weather and road conditions, among others. In addition, 50 in-depth accidents have been investigated and the data collected according the Pendant methodology. For this in-depth methodology detailed information about the accident has been collected, including injuries, vehicle damage, road conditions and road user- behaviour and actions. An accident reconstruction has been carried for each case including the determination of the speeds and driver actions, and the analysis of the contributing factors for the accident. Depending of the accident complexity, different methodologies have been used to analyse these accident, from the classical analytical equations such as Simms and Woods, to the use of detailed computational pedestrian models as those included in the commercial software- PC-Crash-® or Madymo-®. Also one of the goals of our investigation is the development of multibody models and methodologies for the reconstruction of pedestrian accidents. Some of these tools integrated in the commercial software Cosmos Motion-® are presented. The advantages of the different approaches are compared and discussed for some of the accidents investigated. With these tools the impact speed can be determined from the projection distance with analytical tools or PC-Crash-®, but more complex tools should be used to determine speed from the injuries, what is especially important for fatal accidents. The influence of the vehicle geometry and stiffness characteristics is another aspect analysed, where the influence of the vehicle stiffness has been determined using a combined multibody-finite elements approach within the software Madymo-®.
Adverse weather could impair the performance of many important parts in road transportation. In a tropical country, the threats posed by the weather phenomenon can be viewed from a different perspective as the situation may not be as extreme as snow-related problems or excessive temperature in other countries. Specifically in Malaysia, the situation may be underestimated due to several reasons such as the deficiencies in accident reporting and lack of research work. This background research has looked into various publications as well as related data to explain the need of more comprehensive research in the future.
In an on-going project since 2005, ADAC has been analyzing accidents documented by the ADAC air rescue service. The knowledge derived from real-life accidents serves as a basis for new test configurations and assessment criteria. In 2007, ADAC began looking into the feasibility of international data collection. The idea of Global Accident Prevention was born. Three European partner clubs have begun pioneering the project (ÖAMTC, ANWB, and RACC). The aim is to set up an international accident research network to provide a steady stream of information on road accidents. The FIA Foundation supports ADAC in developing and coordinating this initiative.
Den bisherigen Richtlinien zu Verkehrserhebungen ist gemeinsam, dass sie - wenn überhaupt - nur sehr wenige Aussagen zur erreichbaren Datenqualität enthalten. Normative Vorgaben und konkrete Handlungsanweisungen, die zu einer Verbesserung der Datenqualität von Erhebungen führen, fehlen in der Regel für die meisten Erhebungsverfahren. Abgesehen von Einzelaspekten wie beispielsweise den Kernelementen für Haushaltsbefragungen zum Verkehrsverhalten gibt es keine Qualitätsstandards für die Konzipierung, Durchführung und Auswertung einer Verkehrserhebung. Ziel der vorliegenden Studie ist es, mit Blick auf verschiedene Datennutzer und Arten der Datenverwendung wissenschaftlich abgesicherte Qualitätsstandards für Verkehrserhebungen zu erarbeiten. Im Kern sollten Hinweise gegeben werden, durch welche konkreten methodischen Ansätze und praktische Maßnahmen man für die unterschiedlichen Erhebungsverfahren im Verkehrswesen (Zählungen, Messungen, Verhaltensbeobachtungen und Befragungen) die jeweils bestmögliche Datenqualität erreichen kann. Die Ergebnisse dieses Projektes sollen darüber hinaus auch als eine Grundlage für die Fortschreibung der neuen "Empfehlungen für Verkehrserhebungen (EVE)" dienen. Im Kapitel 2 wird zur Schaffung eines geeigneten theoretischen Rahmens nach einer allgemeinen, an den Ansätzen des Qualitätsmanagements orientierten Definition von Datenqualität zunächst ein umfassendes Datenqualitätskonzept dargestellt, welches im Bereich der amtlichen Statistik auf europäischer Ebene entwickelt worden ist. Kapitel 3 stellt wichtige verkehrswissenschaftliche Grundlagen der vorliegenden Untersuchung zusammen. Ausgangspunkt ist eine allgemeine Charakterisierung von Verkehrserhebungen. In Kapitel 4 wird der konzeptuelle Rahmen für die Ermittlung von Standards der Datenqualität dargestellt. Hierzu werden allgemeine Indikatoren der Datenqualität auf Verkehrserhebungen übertragen. Anschließend werden die verschiedenen Anspruchsgruppen und deren Anforderungen an die Datenqualität betrachtet und darauf aufbauend die Elemente einer Qualitätsstrategie für Verkehrserhebungen entwickelt. Wie eine angemessene Datenqualität bei den verschiedenen Arten von Verkehrserhebungen erreicht werden kann, wird in den Kapiteln 5 bis 8 dargestellt. Hier werden Hinweise und Empfehlungen zum Stichprobenverfahren gegeben und es wird aufgezeigt, wie systematische Fehler (Nichterfassung von Stichprobeneinheiten, Fehler bei der Erfassung von Merkmalen, bei der Datenaufbereitung und -auswertung sowie der Darstellung von Ergebnissen) vermieden oder zumindest reduziert werden können. Abschließend werden in Kapitel 9 die wesentlichen Erkenntnisse zusammengefasst und ein Dokumentationsschema vorgestellt, welches einen Orientierungsrahmen für die Durchführung von Verkehrserhebungen liefert.
In India, heavy truck crashes on national highways account for a number of fatalities. But due to lack of in-depth crash data, detailed analysis is not possible to determine injury mechanisms, and to identify infrastructure, vehicle and human factors affecting these crashes. Over the past two years, researchers in India have established a crash investigation network, with the co-operation of the police and hospitals, to conduct crash investigations and in-depth crash data collection on national highways in the state of Tamil Nadu. This pioneering effort has resulted in the development of a heavy truck crash investigation methodology, the outcome of which is scientific and reliable crash data that has been able to provide good insight into truck crashes and their causes. This paper explains the need for truck crash investigations, the methodology, conclusions of the data analyzed up to date, and the need to focus on truck driver working conditions.
Unfortunately, there has been a high number of accident fatalities reported in the Czech Republic in recent years. There are many causes which have led to a growth in the number of road traffic accidents. Since 1990, traffic density has demonstrated an upward moving tendency, daily traffic-jams are on the increase in many cities and traffic capacity on roads and streets is not able to satisfy this increasing density. Moreover, many road users lack experience in terms of driving modern cars. The National Accident Study of the Czech Republic is based on the assumption that the year 2010 is considered as a pilot project with the testing operation of collecting and evaluating data from traffic accidents. From the beginning of 2011, a fully-functional structure of the Traffic Accident Research will be created and solid data generated. Based on this assumption, we hope to begin meaningful cooperation with foreign countries.
A national initiative from the vehicle manufacturers, safety system suppliers, the road administration and universities in Sweden took off in 2007. The aim was to develop a national investigation network and a methodology focusing on all phases of a crash (pre-crash, in-crash and post-crash) as well as all parts of the road transport system (road user, vehicle and road environment). The initiative is formally run as a project with the acronym INTACT (Investigation Network and Accident Collection Techniques). It was a three year pilot with the aim to develop methodologies for an extended national crash investigation activity. During the first year the INTACT partners agreed on the aim for the investigation and methods for retrieving the data were developed. During the second and third year the methodology was tested in real-world investigations and further refinement was made. The paper describes the methodology developed to obtain high qualitative in-depth road crash data.
The role of a national motor vehicle crash causation study-style data set in rollover data analysis
(2010)
On 1 January 2005, The National Highway Traffic Safety Administration, an agency of the United States Department of Transportation, implemented a new data collection strategy designed to assess crash avoidance technologies and report associated behavioral inputs and outcomes. The original goal was a six-year program, however, during the shortened data collection period; it proved a valuable resource for understanding a precrash environment previously obscured by forensic case investigation. Another unintended consequence was an overlap with infrastructure, roadway geometry, and design with the occupant and vehicle outcomes, by virtue of well-defined attributes. External to the collected data, supplementary information was extrapolated, by using manuals published in the United States, by the American Association of State Highway Transportation Officials and selected State Departments of Transportation, in conjunction with the National Motor Vehicle Crash Causation Study (NMVCCS). This provided a backdrop to the infrastructure framework of the rollover problem within which the occupant and vehicle outcomes were studied. If a NMVCCS-style data collection were to be implemented elsewhere, then complementary manuals produced by federal transportation officials might be consulted producing similar relationships. The current study uses NMVCCS data to describe vehicles travelling through diverse design geometries and the outcome for occupants involved in crashes within that system. Codified and extrapolated data form the basis for assessing NMVCCS and its value to the transportation safety community, as the protocols are applicable universally. The benefit in continuing a NMVCCS-style study is noted, as the interaction of roadway infrastructure and occupant protection agencies might find paths to better work together in solving the complex rollover problem using a common data-driven approach.
Accidents with vulnerable road users require special attention within the road safety work because these accidents are often accompanied with severe injuries. Thus In 2006 at least 6200 Powered Two Wheeler (PTW) riders were killed in road crashes in the EU 25 representing 16% of the total number of road deaths while accounting for only 2% of the total kilometers driven. For the prevention of accidents with VRU above all the knowledge of the causes of the accidents is of special importance. This study is based on the methodology of the German In-Depth Accident Study GIDAS. Within GIDAS extensive data on various fields of accidentology are collected on-scene from road traffic accidents with injuries in the Hannover and Dresden area. Using a well defined sample plan the collected data is highly representative to the whole German situation (Brühning et al, Otte et al). The need of in-depth accident causation data in accident research led to the development of a special tool for the collection of such data called ACASS (Accident Causation Analysis with Seven Steps), which was implemented in the GIDAS methodology in 2008 and described by Otte in 2009.
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.
The NHTSA-sponsored Crash Injury Research and Engineering Network (CIREN) has collected and analyzed crash, vehicle damage, and detailed injury data from over 4000 case occupants who were patients admitted to Level-I trauma centers following involvement in motor vehicle crashes. Since 2005, CIREN has used a methodology known as "BioTab" to analyze and document the causes of injuries resulting from passenger vehicle crashes. BioTab was developed to provide a complete evidenced-based method to describe and document injury causation from in-depth crash investigations with confidence levels assigned to the causes of injury based on the available evidence. This paper describes how the BioTab method is being used in CIREN to leverage the data collected from in-depth crash investigations, and particularly the detailed injury data available in CIREN, to develop evidence-based assessments of injury causation. CIREN case examples are provided to demonstrate the ability of the BioTab method to improve real-world crash/injury data assessment.