Sonstige
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.
Traffic accidents were ranked the third among the major causes of death in Thailand. About 13,438 deaths and the death rate from traffic accident was 21.5 per 100,000 of population in 2002. The deaths and death rate varied upon the economic situation. After the economic crisis, traffic accidents were increased as well as the period of the bubble economy. In the Central region of Thailand numbers of road traffic crashes were lower than Bangkok Metropolis, but the highest in the number of deaths, death rate and serious injuries in 2002. Men aged 15"29 years old had higher numbers of deaths than men in other age groups and higher than women. Deaths and injuries from road traffic crashes were the highest in April and January, because there was a long weekend in those months. About 80 percent of road traffic crashes were caused by private car and motorcycle. In 2000 about 51 percent of traffic accidents took place on the straight way, followed by the junction and curves. In 2002, about 97 percent of road traffic crashes were caused by human factors including improper passing, speeding and disregarding to traffic signal, however, the identification of causes of traffic accident needed to improve. Drunk driving, disregarding on safety equipment usage, inefficiency of law enforcement and discontinuing of road safety programs were the deepest causes of traffic accidents. Research based information, a broad coalition of stakeholder and urban planning policy were needed to incorporate for a comprehensive road safety policy formulation and actions.
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.
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.
Safety of light goods vehicles - findings from the German joint project of BASt, DEKRA, UDV and VDA
(2011)
Light goods vehicles (LGVs) are an important part of the vehicle fleet, providing a vital component in the European transportation system. On the other hand, LGVs are in the focus of public discussion regarding road safety. In order to analyse the accident situation of LGVs in an objective manner, Federal Highway Research Institute (BASt), VDA, DEKRA and German Insurers Accident Research (UDV) launched a joint project. The aim of this project, which will be finished by mid of 2011, is to identify reasonable measures which will further improve the safety of LGVs. For the first time, these partners jointly together conducted a research project and put together their know-how in accident research. Analyses are based on real-life accident data from the GIDAS database, the Accident Database of UDV (UDB), the DEKRA database and national statistics. The findings deliver answers to questions within the arena of future legislative actions and consumer protection activities. The analyses of databases cover areas of primary and secondary safety of LGVs with a special focus on advanced driver assistance systems (ADAS), driver behaviour as well as partner and occupant protection. Key figures from national statistics are used to highlight hotspots of accidents of LGVs in Germany. Finally, the proposed countermeasures are assessed regarding their potential effectiveness. Amongst others, the results show that the accident situation of LGVs is very similar to that of passenger cars. Noteworthy variations could be found in collisions with pedestrians, at reversing and regarding accident causes. Occupant safety of LGVs is on a higher level compared to cars. Results indicate that seatbelt use is on a significantly lower level compared to cars. This leads to higher-than-average injury risk for unbelted LGV occupants. When it comes to partner protection, there are problems with compatibility at LGVs. For car occupants there is a very high injury risk when colliding with a LGV. It indicates that higher passive safety test standards for LGVs would be counterproductive if they further increase stiffness of LGVs. The analysis of LGV-pedestrian accidents shows that pedestrian kinematic differs significantly from car-pedestrian accidents. At this point, existing pedestrian related test standards developed for cars cannot be adopted to LGVs. When it comes to active safety, ESC proved its effectiveness once again. Beyond that, rear view cameras, advanced emergency braking systems and lane departure warning systems show a safety potential, too. In addition to any technical countermeasures previously discussed, the importance of the driver behavior and attitude regarding the accident risk was investigated. In order to develop successful actions it is important to understand the main target population. In the case of LGV especially the crafts business and smaller companies are the major contributors the safety issue.
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".
In recent years special attention has been paid to reducing the number of fatalities resulting from road traffic accidents. The ambitious target to cut in half the number of road users who are killed each year by 2010 compared with the 2001 figures, as set out in the European White Paper "European Transport Policy for 2010: Time to Decide" implies a general approach covering all kinds of road users. Much has been achieved, e.g. in relation to the safety of car passengers and pedestrians but PTW accidents still represent a significant proportion of fatal road accidents. More than 6,000 motorcyclists die annually on European roads which amounts to 16% of the EU-15 road fatalities. The European Commission therefore launched in 2004 a Sub- Project dealing with motorcycle accidents within an Integrated Project called APROSYS (Advanced PROtection SYStems) forming part of the 6th Framework Programme. In a first step, the combined national statistical data collections of Germany, Italy, the Netherlands and Spain were analysed. Amongst other things parameters like accident location, road conditions, road alignment and injury severity have been explored. The main focus of the analysis was on serious and fatal motorcycle accidents and the results showed similar trends in all four countries. From these results 7 accident scenarios were selected for further investigation via such in-depth databases as the DEKRA database, the GIDAS 2002 database, the COST 327 database and the Dutch element of the MAIDS database. Three tasks, namely the study of PTW collisions with passenger cars, PTW accidents involving road infrastructure features, and motorcyclist protective devices have been assessed and these will concentrate inter alia on accident causes, rider kinematics and injury patterns. A detailed literature review together with the findings of the in-depths database analysis is presented in the paper. Conclusions are drawn and the further stages of the project are highlighted.
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.
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.
Internationally, the need is expressed for harmonized traffic accident data collection (PSN, PENDANT, etc.). Together with this effort of harmonization, traffic accident investigation moves more and more in the direction of accident causation. As current methods only partly address these needs, a new method was set up. The main characteristics of this method are: • Accident/injury causation (associated) factors can objectively be identified and quantified, by comparison with exposure information from a normal population. • All relevant accident and exposure data can be included: human-, vehicle-, and environmental related data for the pre-crash, crash and postcrash situation (the so-called Haddon matrix). The level of detail can be chosen depending on interest and/or budget, which makes the method very flexible. In this paper the accident collection and control group method are presented, including some of the achieved results from a pilot study on 30 truck accidents and 30 control locations. The data were analyzed by using cross-tabulations and classification-tree analysis. The method proved useful for the identification of statistically significant causational aspects.