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Cyclists are more likely to be injured in fatal crashes than motorised vehicles. To gain detailed and precise behavioural data of road users, i.e. trajectories, a measuring campaign was conducted. Therefore, a black-spot for accidents with cyclists in Berlin, Germany was selected. The traffic has been detected by a fully automated traffic video analysis system continuously for twelve hours. The video surveillance system is capable of automatically extracting trajectories, classifying road user types and precise determining and positioning of conflicts and accidents. Additionally, pre-conflict and pre-accident situations could be analysed to provide further in-depth understanding of accident causation. The evaluation of the measuring campaign comprised the investigation of traffic parameters, e.g. traffic flow, as well as traffic-safety related parameters based on Surrogate Safety Measures (SSM). Furthermore, the spatial and temporal distributions of conflicts involving cyclists were determined. As a result, three possible conflict clusters could be identified, of which one cluster could be confirmed by detailed video analysis, showing conflicts caused by right turning vehicles.
In an on-going project since 2005, ADAC has been analyzing accidents documented by the ADAC air rescue service. The knowledge derived from real-life accidents serves as a basis for new test configurations and assessment criteria. In 2007, ADAC began looking into the feasibility of international data collection. The idea of Global Accident Prevention was born. Three European partner clubs have begun pioneering the project (ÖAMTC, ANWB, and RACC). The aim is to set up an international accident research network to provide a steady stream of information on road accidents. The FIA Foundation supports ADAC in developing and coordinating this initiative.
Active safety systems are aimed at accident prevention, hence the knowledge required for their development is different from that required for passive safety systems aimed at injury prevention. Particularly, knowledge about accident causation is required. When looking at existing accident causation data, it is argued it fails to explain in sufficient detail how and why the accidents occur. Therefore, there is a need for detailed micro-level descriptions of accident causation mechanisms, and also of methodologies suitable for creating such descriptions. One study addressing these needs is the Swedish project FICA (Factors Influencing the Causation of Accidents and Incidents), where an accident investigation methodology suitable for active safety is developed, and in-depth accident investigations following this methodology are carried out on-scene in the area of Gothenburg by a multidisciplinary team. A preliminary aggregated analysis of different cases shows that the methodology developed is adequate for pointing out common contributing factors and devising principal countermeasures.
In Finland all fatal motor vehicle accidents are studied in-depth on-the-spot by multidisciplinary (police, road and vehicle engineers, physician and behavioural scientist) road accident investigation teams (legislation 2001, work started 1968), which operate in every province. The purpose of the teams is to uncover risk factors that turned an ordinary driving situation into a serious accident and give safety recommendations for improving road safety. The investigation teams do not take a stand on guilt or insurance compensation. When analysing accidents the teams use the concepts of key event, immediate, background and injury risk factors. Compiled investigation folders of each case contain investigation forms from each member, preinvestigation protocol, photographs, sketches etc. About 500 items of information are collected from each accident party. The collected information is also coded into a computer database. Both the database and the investigation folders are widely utilized by researchers and authorities conducting safety work.
SEEKING is looking for answers regarding electric powered bicycles and their relation to traffic safety issues. Does a cyclist need "E"? Is it as risky as riding a moped or are E-bikes creating conflicts with other cyclists? The project described herein, funded by the Austrian Ministry of Transport, has the aim of seeking answers to these hot topics. The SEEKING-team shows an in-depth investigation of vehicle dynamic sensing, together with subjective feedback of test riders to detect similarities and differences between conventional cycling and E-biking. Following an overview on the international status quo, measurement runs and their analyses are performed to find a set of preventative measures to make (E-)biking safer. A specific focus is the detection of curve handling, stopping and acceleration phases as well as conflict studies on course-based test rides and "real world" tests on cycling paths (naturalistic riding).
Recent findings from real-world accident data have shown that fatality risks for pedestrians are substantially lower than generally reported in the traffic safety literature. One of the keys to this insight has been the large and random sample of car-to-pedestrian crashes available in the German In-Depth Accident Study (GIDAS). Another key factor has been the proper use of weight factors in order to adjust for outcome-based sampling bias in the accident data. However, a third factor, a priori of unknown importance, has not yet been properly analysed. This is the influence of errors in impact speed estimation. In this study, we derived a statistical model of the impact speed errors for pedestrian accidents present in the GIDAS database. The error model was then applied to investigate the effect of the estimation error on the pedestrian fatality risk as a function of car impact speed. To this end, we applied a method known as the SIMulation-EXtrapolation (SIMEX) method. It was found that the risk curve is fairly tolerant to some amount of random measurement error, but that it does become flattened. It is therefore important that the accident investigations and reconstructions are of high quality to assure that systematic errors are minimised and that the random errors are under control.
While the number of fatal accidents is diminishing every year, there is still a need of improvement and action to prevent these deaths. Basis for this purpose has to be an analysis about the factors influencing the car crash mortality. There are various studies describing the univariate influence of several factors, but crash scenarios are too complex to be described by a single variable. The multivariate analysis respects the interference of the variables and gets so to more detailed and representative results. This multivariate analysis is based on about 2,600 cases (the data have been collected by the accident research units Hannover and Dresden (during the years 1999-2003). This paper presents a multivariate model (containing ten different variables) which detects 93% of these cases properly. This means it detects the cases as truly survived and truly death.
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.
Bicyclists are minimally or unprotected road users. Their vulnerability results in a high injury risk despite their relatively low own speed. However, the actual injury situation of bicyclists has not been investigated very well so far. The purpose of this study was to analyze the actual injury situation of bicyclists in Germany to create a basis for effective preventive measures. Technical and medical data were prospectively collected shortly after the accident at the accident scenes and medical institutions providing care for the injured. Data of injured bicyclists from 1985 to 2003 were analyzed for the following parameters: collision opponent, collision type, collision speed (km/h), Abbreviated Injury Scale (AIS), Maximum AIS (MAIS), incidence of polytrauma (Injury Severity Score >16), incidence of death (death before end of first hospital stay). 4,264 injured bicyclists were included. 55% were male and 45% female. The age was grouped to preschool age in 0.9%, 6 to 12 years in 10.8%, 13 to 17 years in 10.4%, 18 to 64 years in 64.7%, and over 64 years in 13.2%. The MAIS was 1 in 78.8%, 2 in 17.0%, 3 in 3.0%, 4 in 0.6%, 5 in 0.4%, and 6 in 0.2%. The incidence of polytrauma was 0.9%, and the incidence of death was 0.5%. The incidence of injuries to different body regions was as follows: head, 47.8%; neck, 5.2%, thorax, 21%; upper extremities, 46.3%; abdomen, 5.8%; pelvis, 11.5%, lower extremities, 62.1%. The accident location was urban in 95.2%, and rural in 4.8%. The accidents happened during daylight in 82.4%, during night in 12.2%, and during dawn/dusk in 5.3%. The road situation was as follows: straight, 27.3%; bend, 3.0%; junction, 32.0%; crossing, 26.4%; gate, 5.9%; others, 5.4%. The collision opponents were cars in 65.8%, trucks in 7.2%, bicycles in 7.4%, standing objects in 8.8%, multiple objects in 4.3%, and others in 6.5%. The collision speed was grouped <31 in 77.9%, 31-50 in 4.9%, 51-70 in 3.7%, and >70 in 1.5%. The helmet use rate was 1.5%. 68% of the registered head injuries were located in the effective helmet protection area. In bicyclists, head and extremities are at high risk for injuries. The helmet use rate is unsatisfactorily low. Remarkably, two thirds of the head injuries could have been prevented by helmets. Accidents are concentrated to crossings, junctions and gates. A significant lower mean injury severity was observed in victims using separate bicycle lanes. These results do strongly support the extension or addition of bicycle lanes and their consequent use. However, the lanes are frequently interrupted at crossings and junctions. This emphasizes also the important endangering of bicyclists coming from crossings, junctions and gates, i.e. all situations in which contact of bicyclists to motorized vehicles is possible. Redesigning junctions and bicycle traffic lanes to minimize the possibility of this dangerous contact would be preventive measures. A more consequent helmet use and use and an extension of bicycle paths for a better separation of bicyclists and motorized vehicle would be simple but very effective preventive measures.
Who doesn't wear seat belts?
(2009)
Using real world accident data, seat belts were estimated to be 61% effective at preventing fatalities, and 32% effective at preventing serious injuries. They were most effective for drivers with an airbag. Seat belts were estimated as having prevented 57,000 fatalities and 213,000 seriously injured casualties in the UK since 1983. Seat belt legislation was estimated to have prevented 31,000 fatalities and 118,000 seriously injured casualties. A future increase in effective seat belt wearing rate (which takes into account seating position) in the UK from 92.5% to 93% may prevent casualties valued at a societal cost of over -£18 million per year. To target a seat belt campaign, the question "who doesn"t wear seat belts?" must be answered. Seat belt wearing rates and the number of unbelted casualties were analysed. It was primarily young adult males who didn"t wear seat belts, and they made up the majority of unbelted fatalities and seriously injured casualties.
It is very important for Automotive OEMs to get feedback on their product performance on real roads for continuous improvement. Every OEM has a way of collecting this feedback for various performance parameters. Systematic accident research is a way to generate the information related to safety performance of the vehicle. In India, while there is a large amount of data related to the accidents, it is found this data is aimed at understanding the gross statistics and not directly useful for technology development. This paper explains learnings from a pilot study carried out in collaboration with an Emergency Medical Services provider on one of the expressways (motorways). This pilot study has resulted in development of working model that could now be scaled up at for wider application. The paper also presents some of the important observations based on the data collected.
Injuries in motorbike accidents in correlation with protective clothes and mechanism of the accident
(2013)
This study deals with a possible connection between safety clothing / accident mechanism and injury severity in a state-wide traffic accident investigation with focus on light and small motorbike-involvement for accidents in the area of the Saarland in which the persons riding the bike have been injured or killed. An interdisciplinary team of medical scientists and engineers collected the medical and technical data as well as all the relevant traces of the accident on scene and in time. During twenty months of data collection a total of 401 cases could be gathered. Grave injuries were more common for the group of heavier motorcycles (>125 ccm). Motorcyclists had been polytraumatized only in the group where the accident was connected with a collision. Significant correlation between protective clothes and injury severity could only be found for protective gloves and protective trousers. The knowledge about mechanism of the accident, protective clothes and severity of injuries can be helpful for the improvement of road and motorcyclists' safety.
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.
For the avoidance of traffic accidents by means of advanced driver assistance systems the knowledge of failures and deficiencies a few seconds before the crash is of increasing importance. This information e.g. is collected in the German accident survey GIDAS by an interview derived from the ACAS methodology. However to display the whole range of accident causation factors additional information is needed on enduring factors of the system components "human", "infrastructure" and "machine". On the strategic level these accident moderating factors include long term influences such as medical preconditions or a general higher risk taking behavior as well as influences on the immediate conflict level such as an aggressive response to a perceived previous traffic conflict. This study was conducted to examine the feasibility of collecting such causation information in the scope of an in-depth accident investigation like GIDAS. Due to the comprehensive amount of information necessary to estimate the moderating factors the collection of the information is distributed to different methods. 5 cases of real world crashes have been investigated where information was collected on-scene and retrospective by interviews. The identified moderating factors of the accidents and the method for collecting the information are displayed.
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.
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.
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.
Today's volumes of traffic require more and more responsibility from each individual road user in their interactions. Those who drive motor vehicles have the singular obligation to minimise the risk of accidents and hence the severity of injuries, particularly with a view to the most vulnerable road users such as motor bikes, bikes and pedestrians. Since responsible and pro-active driving depends first and foremost on the visual information relayed by our eyes and the visual channel this requires good command of the traffic and all-round visibility from our driver's seat. Granted that human error can never be fully excluded, improving visibility around the car is nevertheless an urgent priority. To do so, we need to rate visibility in the most realistic driving situations. Since the existing visibility metrics and methodology are not applicable to real-life driving situations, this study aimed at developing a new visibility rating methodology based on real-life accident scenarios. On the basis of the cases documented by the accident research project, this study analysed criteria indicative of diminishing visibility on the one hand and revealing some peculiarities in connection with the visibility issue on the other. Based on the above, the project set out to develop a rating methodology allowing to assess all-round visibility in various road situations taking into account both driver and road geometries. In this context, the assessment of visibility while turning a corner, crossing an intersection and joining traffic on a major road (priority through route) is of major importance. The first tests have shown that critical situations can be avoided by adapting the relevant geometries and technical solutions and that significant improvements of road safety can be derived therefrom.
Pedestrian accidents are one of the major concerns related with road accidents around the world. Portugal has one of the highest rates of pedestrian fatalities in Europe. In this paper an overview conditions were the pedestrian accidents occurred in Portugal is presented. In the last years, a project related with the pedestrian accidents has run in Portugal for the period 2004-2006 where 603 people died, 2097 have been severely injured and about 17000 slightly injured. Within this project all the pedestrian accidents in this period have been analysed providing global information about a wide range of aspects, since location, driver and pedestrian characteristics, weather and road conditions, among others. In addition, 50 in-depth accidents have been investigated and the data collected according the Pendant methodology. For this in-depth methodology detailed information about the accident has been collected, including injuries, vehicle damage, road conditions and road user- behaviour and actions. An accident reconstruction has been carried for each case including the determination of the speeds and driver actions, and the analysis of the contributing factors for the accident. Depending of the accident complexity, different methodologies have been used to analyse these accident, from the classical analytical equations such as Simms and Woods, to the use of detailed computational pedestrian models as those included in the commercial software- PC-Crash-® or Madymo-®. Also one of the goals of our investigation is the development of multibody models and methodologies for the reconstruction of pedestrian accidents. Some of these tools integrated in the commercial software Cosmos Motion-® are presented. The advantages of the different approaches are compared and discussed for some of the accidents investigated. With these tools the impact speed can be determined from the projection distance with analytical tools or PC-Crash-®, but more complex tools should be used to determine speed from the injuries, what is especially important for fatal accidents. The influence of the vehicle geometry and stiffness characteristics is another aspect analysed, where the influence of the vehicle stiffness has been determined using a combined multibody-finite elements approach within the software Madymo-®.
In Germany, in-depth accident investigations are carried out in the Hannover area since 1973. In 1999 a second region was added with surveys in Dresden and the surrounding area. Internationally, the acronym GIDAS (German In-Depth Accident Study) is commonly used for these surveys. Compared to many other countries, the sample sizes of the GIDAS surveys are much larger. The goal is to collect 1.000 accidents involving personal injuries per year and region. Data collection takes place by using a sampling procedure, which can be interpreted as a two-stage process with time intervals as primary units and accidents as secondary units. An important question is, to what extend these samples are representative for the target population from which they are drawn. Analyses show, for example, that accidents with persons killed or seriously injured are overrepresented in the samples compared to accidents with slightly injured persons. This means, that these data are subject to biases due to uncontrolled variation of sample inclusion probability. Therefore, appropriate weighting and expansion methods have to be applied in order to adjust or correct for these biases. The contribution describes the statistical and methodological principles underlying the GIDAS surveys with respect to sampling procedure, data collection and expansion. In addition, some suggestions regarding potential improvements of study design are made from a methodological point of view.