Sonstige
Filtern
Erscheinungsjahr
Dokumenttyp
Volltext vorhanden
- ja (45) (entfernen)
Schlagworte
- Ursache (45) (entfernen)
Motorcycle crashes in Austria: Analysis of causes and contributing factors based on in-depth data
(2017)
From CEDATU, the in-depth accident database run by the Vehicle Safety Institute at Graz University of Technology, a representative sample of 101 crashes involving at least one motorcycle was selected. The analysis focused on causes for crashes as well as on contributing factors, but also included parameters of road, riders and vehicles. Own riding speed and "unexpectable action by another road user" were the most frequent causes for accidents. Inappropriate safety distance or delayed reaction were frequent, both as causation factors and as contributing factors. Infrastructure issues never cause an accident, but they are very frequent as contributing factors; road geometry and road guidance are by far most frequent among these. This paper also discusses accidents by type and other parameters (e.g. injury severity by body region, collision speed, age and others), and compares accident causes to previous studies as well as the police reported accident statistics.
Das Fahrverhalten ändert sich mit zunehmendem Alter. Damit ändern sich auch die Risiken. Neben den jungen Fahranfängern im Alter von 18 bis etwa 25 Jahren stellen Fahrer über 75 Jahre eine besondere Problemgruppe dar. Mit zunehmender Zahl alter Fahrer (demographische Entwicklung plus Zunahme der Fahrerlaubnisinhaber in dieser Altersgruppe) besteht hier in naher Zukunft akuter Handlungsbedarf. Ansatzpunkte gibt es im gesamten Mensch-Maschine-Umwelt-System. Fahrzeuge müssen vermehrt im Hinblick auf alte Fahrer konstruiert und optimiert werden. Die Infrastruktur muss den Bedürfnissen einer eindeutigen Verkehrsführung angepasst werden. Aber nur, wenn der Mensch selbst geeignet ist, als Fahrer am Straßenverkehr teilzunehmen, ist ein Gewinn bei der Verkehrssicherheit zu erwarten. Dies muss gewährleistet werden. Wichtig ist, dass die Problematik der alten Fahrer als solche erkannt wird und schnell eine tragfähige Lösung für die Zukunft gefunden wird.
Die Klinik für Frührehabilitation und Geriatrie, Westküstenklinikum Heide ist Bestandteil eines Kooperationsnetzwerks und wirkt am Erhalt der Mobilität und Autonomie älterer Verkehrsteilnehmer im Landkreis Dithmarschen mit. Die Zusammenarbeit mit Seniorenbeiräten, Landesverkehrswacht, Fachdiensten, Polizei-Dienststellen, Ärzten und Psychologen sowie Fahrlehrern ermöglicht eine breite Datenerfassung zum Thema ältere Kraftfahrer, insbesondere zu ihrem Unfallgeschehen.
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.
Die Feststellung empirisch belegten Alkoholkonsums bei Kindern und Jugendlichen, aber nur rudimentärer Dokumentation entsprechender Verkehrsunfälle begründete die vorliegende Untersuchung. Qualitative mündliche Befragungen von Experten und Jugendlichen, Feldbeobachtungen und quantitative schriftliche Befragungen von Jugendlichen führten zu folgenden Ergebnissen: Etwa 65 % der schriftlich befragten 12- bis 22-Jährigen waren vor dem 18. Lebensjahr mindestens einmal im Monat übermäßig alkoholisiert mobil. Mit durchschnittlich 15 Jahren findet nicht nur der erste übermäßige Alkoholkonsum statt, sondern auch die ersten Situationen alkoholisierter Mobilität, vorrangig bei männlichen Jugendlichen. Wenngleich nur rd. 5 % der Befragten eine erlebte gefährliche Verkehrssituation als "echten" Verkehrsunfall bezeichneten, verwiesen immerhin etwa 27 % auf mindestens eine gefährliche Verkehrssituation unter Alkoholeinfluss vor dem 18. Lebensjahr. Von den insgesamt 349 berichteten gefährlichen Verkehrssituationen gingen 113 mit leichten und 24 mit schweren Verletzungen einher. Aber auch die Nichtverletzten verwiesen auf zahlreiche erlebte Gefahren bei ihrer Mobilität unter Alkoholeinfluss. Vorrangig männliche Jugendliche erleben solche Situationen mit durchschnittlich 15,7 Jahren. In mehr als der Hälfte der gefährlichen Verkehrssituationen unter Alkoholeinfluss waren die Akteure alleine unterwegs. Die alkoholisierten Kinder und Jugendlichen verunfallten zumeist als Fahrradfahrer und Fußgänger. In rd. 40 % der Fälle erfolgte eine medizinische Versorgung, von nur rd. 20% dieser Alkoholunfälle erlangt die Polizei Kenntnis. Unterstrichen wird die Notwendigkeit weiterer, differenzierender Untersuchungen, um die explorativ gewonnenen Erkenntnisse zu verifizieren und geeignete Präventionsmaßnahmen zu begründen. Inhaltlich und aufwandsökonomisch wird die ressortübergreifende Zusammenarbeit mit der Bundeszentrale für gesundheitliche Aufklärung empfohlen.
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.
Der Bericht enthält die Beurteilung von schädigungsrelevanten Einwirkungen und Schädigungspotenzialen von Betonbrücken sowie deren Erfassung am Bauteil mithilfe aussagekräftiger Parameter und geeigneter Sensoren im Rahmen des Themenschwerpunkts "Intelligente Bauwerke" der BASt. Die Grundlage zur Beurteilung von Schädigungspotenzialen bildet die Auswertung tatsächlich aufgetretener Schäden an Stahlbeton- und Spannbetonbrücken (97.662 Schäden an 3.474 Brücken). Neben der Aufbereitung der chronologischen Entwicklung von Vorschriften und Normen für den Bau von Brücken wurden Schäden infolge von Planungs- und Entwurfsfehlern, sowie Ausführungsfehlern analysiert. Den Schwerpunkt des Berichts bilden die Darstellung und Bewertung von Schädigungspotenzialen getrennt für die Widerstandsseite(auffällige Bauteile/Konstruktionen) sowie für die Einwirkungsseite (relevante Einwirkungen). Bauteile und Konstruktionen werden dazu im Hinblick auf die Merkmale Standsicherheit, Dauerhaftigkeit und Verkehrssicherheit untersucht. Darüber hinaus werden maßgebende Einwirkungen aus den Umweltbedingungen und insbesondere die Einwirkungen infolge des (Schwer-)Verkehrs bewertet. In einem weiteren Arbeitsschritt werden geeignete Schädigungsmodelle zur Beschreibung bekannter Schädigungsprozesse bei Brücken aus Stahl- und Spannbeton dargestellt und die modellspezifischen Einflussgrößen detailliert aufbereitet. Die Darstellung relevanter Parameter zur Erfassung von Einwirkungen und Schäden an Brückenbauwerken, sowie die Erfassung dieser Parameter mit geeigneten Sensoren bilden einen weiteren Schwerpunkt des Projektes. Darüber hinaus werden die Grundlagen eines Datenerfassungssystems dargestellt und abschließend Genauigkeits- und Häufigkeitsbereiche für die Datenerfassung und die Möglichkeiten der Sensorplatzierung aufgezeigt. Die Zusammenstellung der Ergebnisse erfolgt in Form eines Handbuchs.
Unfälle im Straßenverkehr sind in aller Regel Konsequenzen normalen Fahrverhaltens, das an eine bestimmte Situation nicht angepasst war und daher zum Unfall beigetragen hat. Zur Klassifikation dieses mutmaßlich fehlerbehafteten Verhaltens wurde im hier berichteten Projekt eine Taxonomie entwickelt. Sie dient der Klassifizierung von Fahrerfehlverhalten und integriert Aspekte des menschlichen Informationsverarbeitungsprozesses sowie die drei Fehlertypen von RASMUSSEN (1983). Als Bestimmungsstücke beinhaltet die Taxonomie Fehlertypen (regel-/wissens-/fertigkeitsbasiert) und Entscheidungsknoten mit Fragen, deren Beantwortung den Analysten zum jeweiligen Fehler führt. Zusammengefasst bietet die erarbeitete Taxonomie eine breite Anwendbarkeit für die Klassifikation von Fahrfehlern und fehlerfreiem Verhalten bei Manövern, kritischen Situationen bis hin zu Beinaheunfällen oder Unfällen, z. B. zur Harmonisierung der (Video-)Auswertung von FOT- und NDS-Datensätzen oder für In-Depth-Unfallerhebungen. Die Taxonomie wird komplementiert durch eine Übersicht über Fehlervorläuferbedingungen, die im Sinne von Genotypen (HOLLNAGEL 1998) in ihrer jeweiligen Ausprägung auslösende und begünstigende Bedingungen für Fehler, Beinaheunfälle und Unfälle darstellen. Die Übersicht ist als erweiterbares strukturierendes Dokument zu sehen, welches je nach wissenschaftlichen Erkenntnissen verändert werden kann. Gemeinsam mit der Taxonomie bildet sie die Basis für die Ableitung von Fahrerassistenzbedarf und andere Maßnahmen, zur Generierung von Hypothesen und zur strukturierten Sammlung von Studienergebnissen. Der vorliegende Bericht adressiert die FOT- und NDS-Community sowie allgemein verkehrspsychologisch-wissenschaftlich Interessierte. In acht Kapiteln widmet er sich den Arbeitsschritten und Ergebnissen der Taxonomieentwicklung.
The effect of fatigue on driving has been compared to the effect of alcohol impairment in both driver performance and crash studies. However are crash characteristics and causation mechanisms similar in crashes involving fatigue to those involving alcohol when studied in the real world? This has been explored by examining data held in the EC project SafetyNet Accident Causation Database. Causation data was recorded using the SafetyNet Accident Causation System (SNACS). The focus was on Cars/MPV crashes and drivers assigned the SNACS code Alcohol or Fatigue. The Alcohol group included 44 drivers and the Fatigue group included 47. "Incorrect direction" was a frequently occurring critical event in both the Alcohol and Fatigue groups. The Alcohol group had more contributory factors related to decision making and the Fatigue group had more contributory factors relating to incorrect observations. This analysis does not allow for generalised statements about the significance of the similarities and differences between crashes involving alcohol and fatigue, however the observed differences do suggest that attempts to quantify the effect of fatigue by using levels of alcohol impairment as a benchmark should be done with care.
With an ever rising human life expectancy the share of elderly people in society is constantly rising. This leads to the fact that at the same rate the share of people with age related diseases such as dementia and poor eyesight taking part in traffic will rise and therefore traffic accidents caused by this group of people due to the disease will play an ever greater role. This Situation will be among the future challenges of road safety work. At present this study displays specific characteristics of accidents caused by elderly car drivers (aged 65 or higher) based on the analysis of the German In-Depth Accident Study GIDAS. Herein almost 1000 elderly car drivers were identified as accident participants in the years 2008 to 2011. The focus of this study lies on identifying special types of accidents which are caused by elderly drivers and on characterizing these types with the information gathered on scene and by interviewing the participants. The main evidence analyzed is the knowledge about the accident locality, the trajectories of the participants as well as the reasons for the occurrence of the accidents. Furthermore personal information such as the personal condition before the accident and driving purposes is used to identify patterns of contributing circumstances for accidents caused by elderly traffic participants.
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.
An analysis of NASS and FARS was conducted to determine crash conditions that involved injuries that are not currently being directly addressed by vehicle safety standards or by consumer information test protocols. Analysis of both field data and US NCAP tests were conducted to determine the relative safety provided by seating position and by vehicle model year. Opportunities for improvements were determined by crash categories with large populations of injuries that were not addressed by safety tests or smaller numbers that were increasing in frequency. Areas of opportunities include improved occupant restrain in rollovers, improved frontal protection for rear seat occupants and improved fire prevention in frontal and rollover crashes.
Since 2005, the motorcycle crash fatalities in the US exceeded 10% of the overall annual traffic fatalities. Consequently, it has become critical to gain in-depth understanding of the factors and characteristics contributing to motorcycle crashes. Unfortunately, there currently exists no database gathering the necessary information for an in-depth analysis of the US motorcycle crashes. So this study utilizes the NASS/CDS database (National Automotive Sampling System, Crashworthiness Data System) in order to gain insights into the patterns and factors leading to a NASS/CDS motorcycle crash, from 1997 to 2007. NASS/CDS samples about 5,000 passenger car tow-away crashes per year. Each case includes photographs and detailed data on crash and pre-crash characteristics, vehicle types, trajectories, types of impact, and other pertinent roadway and crash scene information, allowing an in-depth investigation of the crash mechanisms. However, the NASS/CDS sampling process specifically focuses on passenger car crashes, so the cases extracted only correspond to crashes in which a passenger vehicle was towed, and a motorcycle was somehow involved. Thus, a by-hand in-depth review of about 200 cases allowed retrieving 106 relevant crashes for this study, tending to represent the severe passenger vehicle(s) versus motorcycle(s) crashes on US roads. The findings lead to the conclusion that these crashes mostly result from the low conspicuity of the motorcycle, and from the inability of the car drivers to fully appreciate and anticipate the behavior of a motorcycle. Indeed, it has been shown that, first, the car drivers involved in these cases did not attempt any avoidance maneuver, second, they were largely of ages under 25, and finally, the majority of the crashes were in an intersection scenario. In addition, the two major scenarios unveiled were the car attempting a left turn from the opposite direction and the car attempting a left turn from the right. The paper mentions several solutions to enhance the motorcycle- conspicuity and to allow the car drivers to better anticipate its behavior, which seem to be key factors in the intersection-related crashes (and more generally in the passenger vehicle(s) versus motorcycle(s) crashes).
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.
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.
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.
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.
Relevant accident related factors : risk and frequencies of contributing to road traffic accidents
(2009)
In the course of the European Project TRACE (Traffic Accident Causation in Europe) an attempt was made to analyse the cause of road traffic accidents from a factors' point of view. By literature review the most important independent risk factors for traffic accidents were identified to be speed, alcohol intake, male gender, young age, cell phone use, and fatigue. However, the impact of an accident related factor also depends on its prevalence in traffic and accidents, respectively. Available to the Partners in the TRACE Project were different accident databases. Causally contributing factors found by accident investigations that are most often coded in accident databases are connected to unadapted speed and inattention. Taking into account the risk increase and the frequency of contribution to accidents the conclusion can be drawn that the most relevant factors for accident causation are: "alcohol", "speed", and "inattention and distraction".
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.