83 Unfall und Mensch
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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.
In Germany, courses for the restoration of the fitness to drive after licence revocation are provided for different offender groups (alcohol, drug and demerit point offenders). Providers of these courses are by law required to prove the effectiveness of the applied course programs. For the evaluation of effectiveness, the Federal Highway Research Institute (BASt) established specific "Reference Values" in 2002. The objective of the study at hand was to collect valid data in order to renew the old-established Reference Values from 2002. Additionally, data collection aimed at initializing Reference Values for drug offender programs. Over 66,000 drivers were analysed regarding their traffic probation in the three years after licence reinstatement. Offenders were assigned to an offender group (alcohol, drugs and demerit point offenders) based on the reason for prior licence revocation. Different indicators were used as criteria for re-offending: new alcohol or drug records, culpable accident involvement and repeated licence revocation. For each of the offender groups, frequency distributions regarding these indicators were calculated. Frequencies of recidivism are highest for the group of demerit point offenders. Compared to the Reference Values of this group from 2002, frequencies of re-offending increased. Conversely, re-offence frequencies of alcohol offenders are halved compared to the data from 2001. The analysis of the re-offence frequencies of drug offenders reveals an equal amount of re-offenders as in the alcohol offender group. The collected data serve as a good base for renewal of the old-established Reference Values and may be applicable as comparative data for future evaluations The results reveal significant differences between recent data and earlier studies. These may occur due to improvements of the applied programmes, but also due to situational changes, e.g. increased enforcement levels and expansion of the catalogue of offenses which lead to demerit points.
The objectives of this paper are the analysis of the accident risk of drivers brain pathologies (Mild Cognitive Impairment, Alzheimer- disease, and Parkinson- disease), and the investigation of the impact of driver distraction on the accident risk of patients with brain pathologies, through a driving simulator experiment. The three groups of patients are compared to a healthy group of similar demographics, with no brain pathology. In particular, 125 drivers of more than 55 years old (34 "controls"" and 91 "patients") went through a large driving simulator experimental process, in which incidents were scheduled to occur. They drove in rural and urban areas, in low and high traffic volumes and in three distraction conditions (undistracted driving, conversation with a passenger and conversation through a mobile phone). The statistical analyses indicated several interesting findings; brain pathologies affect significantly accident risk and distraction affects more the groups of patients than the control one.
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.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
The bicyclist accidents were analyzed to get better understanding of the occurrences and frequency of the accidents, injury distributions, as well as correlation of injury severity/outcomes with engineering and human factors in two different countries of China and Germany. The accident cases that occurred from 2001 to 2006 were collected from IVAC database in Changsha and GIDAS database in Hannover. Based on specified sampling criteria, 1,570 bicyclist cases were selected from IVAC database in Changsha, and 1806 cases were collected from Hannover, documented in GIDAS database. Statistical analyses were carried out by using these selected data. The results from the statistical analysis are presented and discussed in this study.
A concept for Safe-Driving-Trainings with a focus on risky behavior and safety related attitudes has been evaluated. 519 participants have been tested before and after the training by means of a questionnaire with the topics: technical driving competence, awareness of risks, and propensity for anticipation. A control group (131 subjects) was used to check for the possibility of response artifacts. Three months later, 92 members of the treatment group and 25 members of the control group have been tested again. The results show significant positive changes in driving competence, risk awareness, and safety related attitudes, especially anticipation, due to the training. Compared to the control group the participants have become more risk aware and they regard of risk avoiding behavior as more important. The results show that this concept for Safe-Driving-Trainings has not only short-term but, more importantly, long-term positive effects on the safety-relevant attitudes and cognitions of young drivers.
Rural roads (highways) in Germany have to provide both high road safety and an appropriate level of service in accordance with their function in the road network. Single carriageway rural roads often underperform these expectations. An analysis of severe accidents on rural roads found two main contributing factors. First, high or inappropriate speed leads to accidents caused by the loss of control of the vehicle. Second, unsafe passing manoeuvres related to a misjudgement of sight distance, speed of oncoming vehicles or a misjudgement of the driver vehicle's acceleration capability. On the five roads where unsafe passing manoeuvres were a main contributing factor to accident occurrence, single short passing lanes (600 m to 1.2 km) were built to provide safe passing. On the remaining two-lane sections passing was prohibited by road signs and road marking. This paper investigates the effect of this design change on the accident situation and on traffic flow. The research project is based on a before/after comparison of traffic and accident data. Traffic volume, vehicle types and their velocities as well as the time gaps between the vehicles were recorded at different cross-sections. The result shows a significant improvement in road safety. This improvement was especially noted for severe head-on crashes, which were reduced to almost zero. The analysis of traffic flow on these roads pointed out that the chosen lengths of passing lanes were sufficient for safe passing and thereby reduced the need for dangerous driving behaviour. The recommendations of this research were fundamental for the determination of the design parameters of the second highest design class (EKL 2) in the new German Rural Road Design Guideline (RAL) published in spring 2013.
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.
Side impacts, both nearside and farside, have been indicated by research to be responsible for a large proportion of serious injuries from road crashes. This study aimed to compare and contrast the characteristics of nearside and farside crashes in Australia, Germany and the U.S., using the ANCIS, GIDAS and NASS/CDS in-depth-databases, in order to establish the impact and injury severity associated with these crashes, and the types of injuries sustained. The analyses revealed some interesting similarities, as well as differences, between both nearside and farside crashes, and the emergent trends between the three investigated countries. More specifically, it was indicated that whilst the severity of injury sustained in nearside crashes was slightly greater overall than that found for farside crashes, careful consideration of struck and nonstruck side occupants must be made when considering aspects such as vehicle design and occupant protection.