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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.