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One goal of the assessment of the crashworthiness of passenger cars is to characterize the potential of injury outcome to occupants of cars involved in an accident. This can be achieved by the help of an index that puts the number of injured occupants of passenger cars in relation to the number of cars involved in an accident. As a consequence, this index decreases with a lower potential of injury and rises with a higher number of injuries while assuming a fixed number of accidents. Another index is introduced that uses an economical weighting of each injury level. The consequential injury costs are calculated using the average economical costs for lightly, severely and fatally injured persons. The calculation of the safety indices is based on an anonymized sample of accident data provided by the Federal Statistical Office. An index of Mercedes passenger car drivers depending on the year of registration between 1991 and 2006 is compared to the index of drivers of cars of other makes within the same range of registration years.
This paper uses the national accident statistics of Great Britain to evaluate the effectiveness of Electronic Stability Control Systems (ESC) to reduce crash involvement rates. The crash experience of 8,951 cars is analysed and compared to a closely matching set of non-ESC cars using case-control methods. This is one of the largest ESC samples analysed to date. Overall the cars with ESC are involved in 3% fewer crashes although the effectiveness is substantially higher under conditions of adverse road friction. ESC equipped cars are involved in 15% fewer fatal crashes although this reduction represents the combined effect of ESC and passive safety improvements.
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 GIDAS-investigation team of Dresden (VUFO) has documented more than 11.500 accidents since 1999. The documentation of the accident includes beside vehicle-, injury- and environmental-data very detailed reconstruction data. Within this accident investigation the VUFO began to record the skid resistance of the accident site in 2009. The measurements are divided in macro- and microroughness (Sand depth method and Portable Skid Resistance Tester-SRT-by Munro-Stanley London-©). Both methods are used to determine the skid resistance for more than 1000 passenger cars. The aim of the present study is to find out a relationship between the measured skid resistance, the road conditions and the friction coefficient, which is used to calculate the maximum accelerations and decelerations during a reconstruction of an accident. Basic approach to convert the SRT-value into the friction coefficient is the calculation of the theoretical absorbed energy of the spring rubber system of the swinging arm of lever. This absorbed energy is used to get the friction coefficient by using the equations for the work of friction. To consider the road-behavior, in correlation to the friction coefficient, the results will be merged with existing literature. Last step for this study will be a comparison between actual used friction coefficients all over the GIDAS-database and the theoretical results. The study shows, if it is possible to use the SRT-Measurement for the estimation of a friction coefficient for the reconstruction of a traffic accident. As expected, the GIDAS-Database and the additional measurement of the roughness of the road directly on the spot are an enormous useful dataset.
The purpose of this study was to analyse the actual injury situation of bicyclists regarding accidents involving more than one bicyclist. Bicyclists were included in a medical and technical analysis to create a basis for preventive measures and discovered repeating accident patterns and circumstances such as daytime, environment, helmet use rate. Technical and medical data were collected at the scene, shortly after accident. The population was compared focusing on bicycle versus bicycle accidents. Technical analysis included speed at crash, type of collision, impact angle, environment, used lane and relative velocity. Medical analysis included injury pattern and severity (AIS, ISS). Included were 578 injured bicyclists in 289 accidents from years 1999 to 2008, 61 percent were male (n=350) and 39 percent female (n=228). Sixty-seven percent ranged between 18 to 64 years of age, twelve percent each between 13 to 17 years of age and older than 65 years, eight percent between 6 to 12 years and one percent between 2 to 5 years.. Crashes took place in urban areas in 92 percent, in rural areas in 8 percent. Weather conditions were dry lanes in 97 percent and wet conditions in 3 percent. Eighty-three percent of all accidents happened during daytime, ten percent during night, and seven percent during dawn. The helmet use rate was only 7,5 percent in all involved bicyclists. The mean Maximum Abbreviated injury scale, Injury severity score was 1,31. Bicyclists are still minimally- or unprotected road users. The helmet use rate is unsatisfactorily low. The incidence of bicycle to bicycle crashes is high. Most of these accidents take place in urban areas. The level and pattern of injuries is moderate. Most of the more severe injuries occur to the head and could have been avoided by frequent helmet use.
Bei Straßenverkehrsunfällen werden volkswirtschaftliche Ressourcen vernichtet und die Leistungsfähigkeit des Wirtschaftssystems entsprechend beeinträchtigt. Die Bewertung der volkswirtschaftlichen Schäden ist unerlässlich, um Maßnahmen zur Verringerung von Straßenverkehrsunfällen beurteilen zu können. Das Bewertungsverfahren zur Ermittlung der volkswirtschaftlichen Kosten durch Straßenverkehrsunfälle wurde in den letzten Jahren sowohl für Personen- als auch für Sachschäden überarbeitet. Mit dem neuen Verfahren wurde das Unfallgeschehen von 1995 bis 1998 bewertet. Die Entwicklung der Unfallkosten zeigt, dass eine erfolgreiche Verkehrssicherheitspolitik zu einer erheblichen Kostenentlastung der Volkswirtschaft und entsprechender Steigerung der Lebensqualität beitragen kann. Allein im betrachteten Zeitraum von 4 Jahren haben Straßenverkehrsunfälle volkswirtschaftliche Kosten in Höhe von fast 280 Milliarden DM verursacht. Diese Kosten sind ein Beleg dafür, dass die Verbesserung der Verkehrssicherheit eine verkehrspolitische Daueraufgabe ersten Ranges bleibt. Gleichzeitig wurden nach Ortslagen differenzierte Unfallkostensätze ermittelt, die als Eingangsdaten für gesamtwirtschaftliche Wirtschaftlichkeitsanalysen von Straßenverkehrsmaßnahmen - zum Beispiel nach den "Empfehlungen für Wirtschaftlichkeitsuntersuchungen von Straßen" (EWS 97) - dienen.
Die Europäische Union hat sich zum Ziel gesetzt, die Anzahl der Getöteten im Straßenverkehr bis zum Jahr 2010 zu halbieren. Um dieses Ziel zu erreichen, ist es notwendig, sinnvolle Prioritäten zu setzen und effektive Straßenverkehrssicherheitsmaßnahmen umzusetzen. Den Entscheidungsträgern dient die ökonomische Bewertung dieser Maßnahmen als sachliches Kriterium bei der Auswahl der umzusetzenden Sicherheitsmaßnahmen. Nachfolgend wird ein Überblick darüber gegeben, wie Straßenverkehrssicherheitsmaßnahmen ökonomisch bewertet werden können, welche methodischen Prinzipien hierbei beachtet werden müssen, welche Daten notwendig sind und dem Evaluator zur Verfügung stehen und welche Barrieren bei der Bewertungsarbeit auftreten können. Darüber hinaus werden Beispiele bewerteter Maßnahmen und eine Kurzfassung über den Themenbereich der ökonomischen Bewertung in Form einer Power-Point Präsentation dargestellt. Die nachfolgend dargestellten Erkenntnisse wurden im Rahmen des EU Projekts ROSEBUD gewonnen.
From literature well-known analyzes on risks, hazards and causes of accidents of older drivers are amended by the present study in which a comparison of the specific features of accident causes of older car drivers (older than 60 years) and of younger car drivers (under 25 years) is conducted. Mainly the question is pursued if specific errors, mistakes and lapses are predominant in the two different age groups. The analysis system ACAS (Accident Causation Analysis System) used hereby consists of a sequential system of accident causation factors from the human, the technical and the infrastructural field, whereupon for this study the influence of the human features on the accident development in two different age groups is of interest. ACAS is both an accident model and an analysis and classification system, which describes the human participation factors of an accident and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. In five steps (categories) of a logical and temporal sequence the hierarchical system makes human functions and processes as determinants of accident causes identifiable. The methodology specifically focuses on the use in so-called "In-Depth" and "On-Scene" investigation studies. With the help of the system for each accident participant one or more of five hypotheses of human cause factors are formed and then specified by appropriate verification criteria. These hypotheses in turn are further specified by indicators in such manner that the coding of the causation factors by a code system meets the needs of database processing and are accessible to a quantitative data analysis. The first results of the descriptive comparison of the two age groups concern mainly differences in the functional levels "information admission/perception" (where the elderly drivers have more difficulties than the young ones) and "information processing/evaluation" (where the younger drivers show more problems). Concerning the cognitive function of "planning" the group of younger drivers seems to be more often involved in an accident because of excessive speed.
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.
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.