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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.
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.
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.
To determine whether the model "Accompanied driving from age 17" (AD17) contributes to improvement of young drivers' road safety, two large random samples of novice drivers drawn from the Central Register of Driving Licences (ZFER) held at the Federal Motor Transport Authority (KBA) were compared in terms of the rates of accident involvement and traffic offences at the start of their solo driving career. The samples comprised former participants in the AD17 model and novice drivers of the same age who had obtained a driving licence in the conventional manner immediately after their 18th birthday. Both analysis groups were contacted by post and asked to complete an online questionnaire. In response, 19,000 drivers reported on their first year of solo driving and on the occurrence of any accidents or traffic offences during this period. The analyses were repeated with two "silent" analysis groups comprising a total of 75,000 drivers, for whom any records of traffic offences were retrieved from the Central Register of Traffic Offenders (VZR), with a distinction being made between offences in connection with an accident and other offences. The AD17 model was introduced in all 16 German federal states between April 2004 and January 2008. By the end of 2009, almost one million novice drivers had participated in the model, and almost three-quarters of the target group - so-called "early beginners" who wished to commence solo driving immediately after reaching the age of 18 years - opted for the AD17 model. The phase of introduction of the model was associated with a temporary increase of around five per cent in the demand for driving licences from persons under 19 years of age. During the first year of solo driving, the rate of accident involvement for AD17 participants was 19 per cent lower and the rate of traffic offences 18 per cent lower than for drivers of the same age who had obtained their driving licence in the conventional manner. After adjustment for confounds (e.g. gender and vehicle availability), a reduction in accidents by 17 per cent and in traffic offences by 15 per cent remained as an effect attributable to the model. A comparison on the basis of the distances driven indicated 22 per cent fewer accidents and 20 per cent fewer traffic offences. The results are statistically significant and apply to both male and female drivers. The findings were confirmed in the replication study based on VZR data, with one exception: For female AD17 drivers, and here only for VZR-recorded offences excluding accidents, no significant reduction was found. On the other hand, the rate for female drivers is already lower than that of their male counterparts by three-quarters. Approximately 1,700 injury accidents were prevented by implementation of the model in 2009.
Das Risiko, bei einem Verkehrsunfall verletzt oder getötet zu werden, ist in der Gruppe der 18- bis 24-Jährigen deutlich größer als in allen anderen Altersgruppen. Diese Tatsache besitzt trotz eines deutlichen Rückgangs der Zahl der Verletzten bzw. Getöteten in dieser Altersgruppe in den vergangenen zehn Jahren weiterhin Gültigkeit. Somit bleibt die Verbesserung der Verkehrssicherheit insbesondere für die 18- bis 24-Jährigen auch in Zukunft ein vordringliches gesellschaftliches Anliegen. Im Rahmen einer Repräsentativbefragung (N=2084) wurde der Frage nachgegangen, in welchem Zusammenhang Erwartungen, Motive und Erfahrungen sowie weitere psychologische Merkmale (z.B. Lebensstile) und bestimmte Lebensumstände mit dem Fahrstil und dem Unfallrisiko junger Fahrerinnen und Fahrer stehen. Zur Beantwortung dieser Frage wurde ein theoretisches Modell entwickelt, das Bezüge zu verschiedenen etablierten Theorien der Psychologie aufweist. Die vorliegende Studie knüpft an älteren Studien an, aus denen hervorging, dass die Zielgruppe der jungen Fahrerinnen und Fahrer im Hinblick auf die Gefährdung im Straßenverkehr ausgesprochen heterogen ist und sich die Lebensstile der Personen zur Identifikation von Risikogruppen sehr gut eignen. Deshalb wurde eine Aktualisierung der Lebensstil-Typologie vorgenommen und ihre Relevanz im Hinblick auf eine Identifikation von Risikogruppen untersucht. Zur zusätzlichen Beschreibung dieser Gruppen wurden - theoretisch abgeleitet - zahlreiche verkehrssicherheitsrelevante Merkmale herangezogen, die bislang in diesem Forschungsfeld keine oder nur eine geringe Berücksichtigung gefunden haben. Hierzu wurden u.a. eigene Skalen entwickelt, die sich als ausgesprochen zuverlässig erwiesen haben. Eine Clusteranalyse ergab sechs Lebensstilgruppen, die sich hinsichtlich der Gefährdung im Straßenverkehr deutlich voneinander unterscheiden und eindeutig durch die Ausprägung bestimmter psychologischer, demographischer und sozioökonomischer Merkmale beschreibbar sind. Die stärkste Gefährdung kristallisiert sich beim "autozentrierten Typ" heraus, der mit einem Anteil von 10 % an der Gesamtgruppe der jungen Fahrerinnen und Fahrer vertreten ist. Diese Lebensstilgruppe hat sowohl den mit Abstand höchsten Anteil an Unfallbeteiligten (39 %) als auch den deutlich höchsten Anteil an Personen mit mindestens einem Punkt im Verkehrszentralregister. Für zwei weitere Lebensstilgruppen liegt der Anteil der Unfallbeteiligung bei 20 % oder darüber, für drei Lebensstilgruppen unter 20 %. Beim so genannten "kicksuchenden Typ" zeigt sich mit 15 % der geringste Anteil Unfallbeteiligter. Im Rahmen eines Querschnittsvergleichs wird eine relativ große Stabilität der Lebensstilgruppen über einen Zeitraum von dreizehn Jahren belegt. Hierzu wurden die 18- bis 24-Jährigen aus dem Jahr 1996 (Studie 1) mit den 31- bis 37-Jährigen aus dem Jahr 2010 (Studie 2) verglichen. Beide Gruppen gehören demnach der gleichen Generation bzw. der gleichen Geburtskohorte an. Die Stabilität zeigt sich sowohl im Hinblick auf die Gruppen bildenden Lebensstilmerkmale (z.B. Freizeitverhalten) als auch in der Ausprägung verkehrssicherheitsrelevanter Merkmale in den jeweiligen Lebensstilgruppen. Andererseits jedoch haben sich innerhalb von dreizehn Jahren auch eine Reihe von Ausdifferenzierungen herausgebildet, die zum Teil markante Veränderungen innerhalb der Lebensstilgruppen erkennen lassen. Der auffälligste Unterschied zwischen den beiden Studien ist die Identifikation des "autozentrierten Typs" in 2010. Abschließende Pfadanalysen bestätigen über alle Lebensstilgruppen, über zwei Altersgruppen und über beide Geschlechter hinweg eine sehr gute Anpassung eines theoretischen Modells an die empirischen Daten. Damit besteht ein wichtiger empirischer Beleg für den signifikanten Einfluss von Einstellungen, der erwarteten Handlungskompetenz und von verschiedenen Temperamentsdimensionen auf das berichtete Verhalten und die Unfallbeteiligung junger Fahrerinnen und Fahrer. Insgesamt zeichnen sich die Beschreibungen der sechs Lebensstilgruppen durch einen hohen Differenzierungsgrad aus. Damit ist eine breite empirische Grundlage für die Entwicklung von Verkehrssicherheitsmaßnahmen sowohl für die Gesamtgruppe der 18- bis 24-Jährigen als auch für bestimmte Zielgruppen innerhalb der Gesamtgruppe (z.B. bestimmte Lebensstiltypen, Fahranfänger) gegeben. Darüber hinaus liegen nunmehr auch aktuelle Kenntnisse über die Vergleichsgruppe der 25- bis 37-Jährigen vor, die bei der Entwicklung von Verkehrssicherheitsmaßnahmen für diese Zielgruppe ebenfalls berücksichtigt werden können.
Die Studie beschreibt auf der Grundlage umfangreicher Erhebungsdaten die Pkw-Mobilität von Fahranfängern im ersten Jahr ihrer selbstständigen Fahrkarriere. Die Daten wurden an einer bundesweiten Zufallsstichprobe per einmaliger schriftlicher Befragung in einer Sommer- und einer Winterwelle erhoben. Die Verwendung von Wochenprotokollen mit tagbezogener Dokumentation erlaubt eine Betrachtung einzelner Zeitabschnitte (Tage, Wochen, Monate, Quartale, gesamtes erstes Jahr) und des Mobilitätsverlaufs. Insgesamt liegen der Studie 4.375 auswertbare Fragebogen zugrunde. Neben Basisdaten zu Umfang und Entwicklung der Fahrleistung wurden Daten zu Fahrtzielen, Mitfahrern, befahrenen Straßenarten, Fahrbedingungen, Motiven des Autofahrens, Charakteristika der gefahrenen Pkw, Unsicherheiten im Straßenverkehr, Verkehrsverstößen und ihrer Sanktionierung sowie zur Beteiligung an Verkehrsunfällen erhoben. Auf dieser Grundlage wurden charakteristische Ausprägungen der Mobilität und der Mobilitätsentwicklung für die Gesamtstichprobe sowie für Subgruppen, die nach soziodemographischen Merkmalen und nach Fahrerlaubnisbesitzdauer gegliedert sind, aufgezeigt. Männliche Fahranfänger erbringen am Anfang des ersten Jahres ihrer selbstständigen Pkw-Mobilität geringere Fahrleistungen als gegen Ende dieses Zeitraums. Der aus der Verlaufsbetrachtung des Unfallrisikos bekannte initiale Gefährdungsschwerpunkt fällt für Männer bei fahrleistungsbezogener Betrachtung danach noch gravierender aus. Auf der Grundlage der Merkmale Geschlecht, Alter bei Fahrerlaubniserwerb, Stadt/Land und Berufsbereich wurden clusteranalytisch fünf Fahranfängertypen ermittelt und jeweils relevante Risikomerkmale (Verkehrsverstöße, Unfälle) und Risikoindikatoren (Wochenendmobilität, Extramotive, Fahrleistung/Exposition) ausgewiesen. Es zeigt sich, dass die gängigen Risikoindikatoren (jugendspezifische Wochenendmobilität, "Extramotive") nicht zu einer angemessenen Bestimmung des Verkehrsrisikos von Fahranfängern ausreichen.
Zur Frage, ob das "Begleitete Fahren ab 17" (BF17) zur Verkehrssicherheit junger Fahrer beiträgt, wurden zwei große Zufallsstichproben von Fahranfängern aus dem im Kraftfahrt-Bundesamt geführten Zentralen Fahrerlaubnisregister hinsichtlich ihrer Verkehrsauffälligkeit am Beginn ihres selbstständigen Fahrens verglichen: ehemalige BF17-Teilnehmer und gleichaltrige Fahranfänger mit herkömmlichem Erwerb eines Pkw-Führerscheins unmittelbar nach ihrem 18. Geburtstag. Beide Untersuchungsgruppen wurden postalisch um Teilnahme an Internet-Befragungen gebeten. 19.000 Pkw-Fahrer berichteten von ihrem ersten Jahr des selbstständigen Fahrens, dazu von Verkehrsverstößen und Verkehrsunfällen. Wiederholt wurde die Untersuchung an zwei "stillen" Untersuchungsgruppen mit zusammen 75.000 Fahrern durch Abfrage ihrer Verkehrsverstöße im Verkehrszentralregister (VZR), getrennt nach solchen mit Unfällen und ohne Unfälle. Das BF17-Modell wurde zwischen April 2004 und Januar 2008 in allen 16 Bundesländern in Deutschland eingeführt. Bis Ende 2009 hatten fast eine Million Fahranfänger an ihm teilgenommen. Zu diesem Zeitpunkt entschieden sich fast drei Viertel der Zielgruppe " sogenannte Früheinsteiger, die das selbstständige Fahren unmittelbar mit dem Erreichen von 18 Jahren anstreben - für das BF17. Dabei ist es in der Einführungsphase des BF17 zu einer temporären etwa fünfprozentigen Nachfragesteigerung nach Pkw-Führerscheinen bei den unter 19-Jährigen gekommen. Im ersten Jahr des selbstständigen Fahrens zeigen BF17-Absolventen 19 % weniger Unfallbeteiligungen und 18 % weniger Verkehrsverstöße im Vergleich zu gleichaltrigen Fahrern mit herkömmlichem Führerscheinerwerb. Nach Berücksichtigung konfundierender Faktoren (u.a. Geschlechtszugehörigkeit, Fahrzeugverfügbarkeit) verbleibt eine maßnahmenbedingte Verringerung der Unfälle um 17 % und der Verkehrsverstöße um 15 %. Bei Berücksichtigung der Fahrleistung verringern sich die Unfälle um 22 % und die Verkehrsverstöße um 20 %. Die Ergebnisse sind statistisch signifikant und gelten für Männer wie Frauen. Dies bestätigt sich in der Wiederholungsuntersuchung auf Basis der VZR-Daten mit einer Ausnahme: Für die ehemaligen BF17-Fahrerinnen und hier allein für die VZR-Verstöße ohne Unfall ist keine signifikante Reduktion festzustellen. Allerdings liegt deren Zahl ohnehin schon um drei Viertel niedriger als bei den Männern. Rein rechnerisch gesehen, verhinderte das BF17 im Jahr 2009 rund 1.700 Unfälle mit Personenschaden.
The paper presents a methodology for the benefit estimation of several secondary safety systems for pedestrians, using the exceptional data depth of GIDAS. A total of 667 frontal pedestrian accidents up to 40kph and more than 500 AIS2+ injuries have been considered. In addition to the severity, affected body region, exact impact point on the vehicle, and the causing part of every injury, the related Euro NCAP test zone was determined. One results of the study is a detailed impact distribution for AIS2+ injuries across the vehicle front. It can be stated, how often a test zone or vehicle part is hit by pedestrians in frontal accidents and which role the ground impact plays. Basing on that, different secondary safety measures can be evaluated by an injury shift method concerning their real world effectiveness. As an example, measures concerning the Euro NCAP pedestrian rating tests have been evaluated. It was analysed which Euro NCAP test zones are the most effective ones. In addition, real test results have been evaluated. Using the presented methodology, other secondary safety like the active bonnet (pop-up bonnet) or a pedestrian airbag measures can be evaluated.
Accidents involving two wheels vehicles represent one of the more important types of accidents in Europe. These accidents are usually not easy to reconstruct specially for the analysis of the injuries and its correlation with accident dynamics and evidences. Different methodologies are applied in this work for the reconstruction of two wheeler accidents, especially accident involving motorcycles. From the typologies of road evidences like skid marks, to the use of Pc-Crash and the use of Madymo models, different reconstruction of real accidents are presented. One of the questions that sometimes arise for legal purposes when some type of head injuries arise is if the occupant was wearing or not a helmet. The correlation of head injuries with the use of the helmet is a very important issue, therefore an important legal aspect. One of the key questions for the reconstructions that is difficult to analyze, is if the vehicle occupant, was or not, wearing the helmet. Based on the previously collected information, a generic model of a helmet was developed on CAD 3D, followed by its conversion into finite elements, all in order to perform impact tests using the Madymo software that would help improve the helmet- safety, but that also can be used as a tool in accident reconstruction.
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.
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.
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".
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.
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.
Nigeria ranks one of the highest countries in the world with the largest accident, especially when measured by whiplash associated disorders, whereas, traffic safety education rate, data and information been widely known as preventive indicators have been grossly neglected. In Nigeria, traffic safety enlightenment, awareness, political understanding and appreciation of the problem's magnitude are lacking. This study, therefore, seeks to understand and document the fact that accident causation factors in Nigeria relate more to the problem of development, poverty, knowledge and education as evidenced in most other developing countries. Among the primary accident causation factors on Nigerian roads are: - lack of a transportation system or multi-model integration - sub-standard and obsolete vehicles and road furniture - poor road maintenance, investment and engineering management - paucity of road users' and drivers' knowledge, skill, enlightenment and education of the road Use This paper submits that Nigeria being a developing nation requires purely primitive strategies being cost effective (health wise) than curative measures. It is in this light that an enduring, comprehensive and sustainable traffic safety educational programmes information base and data inventory, analysis and implementations form the focus of this study. This effort will provide basic guidelines framework and implementation procedure for a successful prevention of whiplash associated disorder resulting from road traffic crashes in Nigeria and other parts of the world.
This contribution introduces a number of psychological methods of analysis that are based on the practice-oriented collection of information directly at the site of an accident and that allow for an analysis and coding of the accident causes. Investigation examples and examples of the data combinations with basic medical and technical data are outlined. Objective of the collection is the inter-disciplinary investigation of human factors in the causes of accidents ("human-factor-analysis"). The psychological data are incorporated according to an integrative model for accident causes based on empiric algorithms in the data base of the accident research, where the clustered evaluation potential of comprehensive factors of the accident development can be illustrated. The central theoretical concept for the basic model of the progress of the accident from a psychological point of view comprises psychological indicators for the evaluation of the site of the accident for the analysis of the perception conditions as well as a classification of the gleaned data into the accident progress model according to chronological and local criteria. Perception conditions, action intentions and executions as well as conditions limiting perception and actions are acquired, using a questionnaire for persons involved in an accident, and are also integrated into the data structure concerning weighted feature characteristics as well as combined with other relevant features. Suitable systematization tools for the collection and coding of psychological accident development parameters have to be provided, which require primarily a model image of the corresponding processes from the persons involved in the accident (perceptions, expectations, decisions, actions). The interactive accident model contains components of the models by KÜTING 1990, MC DONALD 1972, SURREY 1969 and RASMUSSEN 1980. Based on the inter-action of the three partial systems "person", "vehicle" and "environment", the first step is the assessment of the situation by the persons involved in the accident. This is dependent on the personal attitudes and motives, on experiences and expectations concerning the progress of the situation. Subsequently, data concerning the manner of the coping with the ambiguous state as well as with the instable state (emergency reaction immediately before the accident occurs) are collected. The factors relating to the persons involved in the accident are gathered on several levels using corresponding questionnaires. The coding of the found and collected characteristics is conducted in a multidimensional evaluation relating to the technical results of the accident reconstruction and of the psychological classification, which are subsequently integrated in coded form into the data base of the accident research. The result of this analysis is a description of the development of the accident depicted on a chronological vector from a perception and decision theoretical perspective. This is explained in detail using exemplary cases.
Interaction of road environment, vehicle and human factors in the causation of pedestrian accidents
(2005)
The UK On-the-Spot project (OTS) completed over 1500 in-depth investigations of road accidents during 2000-2003 and is continuing for a further 3 years. Cases were sampled from two regions of England using rotating shifts to cover all days of the week and all hours of the day and night. Research teams were dispatched to accidents notified to police during the shifts; arrival time to the scene of the accident was generally less than 20 minutes. The methodology of OTS includes sophisticated systems for describing accident causation and the interaction of road, vehicle and human factors. The purpose of this paper is to describe and illustrate these systems by reference to pedestrian accidents. This type of analysis is intended to provide an insight into how and why pedestrian accidents occur in order to assist the development of effective road, vehicle and behavioural countermeasures.
76 severe traffic accidents had been investigated in depth in an ongoing Volkswagen-Tongji University joint accident research project in JiaDing district, Shanghai, PR China since June 2005. With a methodology similar to German accident research units in Dresden and Hannover, a research team proceeds to the scene immediately after the incident to investigate and collect various data on environment, accident occurrence, vehicle state and deformations as well as injuries. The data combined with the results of accident reconstruction will be stored in a database for further statistical and casuistic analysis. The first outcome of the project supports the hypothesis that a main causation for the large number of traffic accidents in China is the lacking of risk awareness in Chinese driver behaviour. Low seat-belt use and the high proportion of vulnerable and poorly protected two-wheelers in traffic are reasons for the high injury and fatality rate in China. The research work shows that accident research in China is feasible and able to give support to tackle one of the urging problems in Chinese development.
The "Seven Steps Method" is an analysis and classification system, which describes the human participation factors and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. By means of the "seven steps" it is possible to describe the relevant human causes of accidents from persons involved in the accident in an economic way with a sufficient degree of exactitude, because the causes can be further differentiated in their value (e.g. diversion as external diversion with regard to impact due to surroundings) and their sub values (e.g. external diversion with regard to impact due to surroundings in the shape of a "capture" of the perception by a prominent object of the traffic environment). Theoretically it is possible that one or more causing moments can be assigned to a person involved in an accident in each of the "seven steps"; however it is also possible to sufficiently clarify the cause in only one level (examples for this are described). In the practice of accident investigation at the site of the accident, the sequence chart is also relevant. With its assistance the questioning of the people involved in an accident can be accomplished in a structured way by assigning a set of questions to each step.