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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.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.
Injury probability functions for pedestrians and bicyclists based on real-world accident data
(2017)
The paper is focusing on the modelling of injury severity probabilities, often called as Injury Risk Functions (IRF). These are mathematical functions describing the probability for a defined population and for possible explanatory factors (variables) to sustain a certain injury severity. Injury risk functions are becoming more and more important as basis for the assessment of automotive safety systems. They contribute to the understanding of injury mechanisms, (prospective) evaluation of safety systems and definition of protection criteria or are used within regulation and/or consumer ratings. In all cases, knowledge about the correlation between mechanical behavior and injury severity is needed. IRFs are often based on biomechanical data. This paper is focusing on the derivation of injury probability models from real world accident data of the GIDAS database (German In-depth Accident Study). In contrast to most academic terms there is no explicit term definition or definition of creation processes existing for injury probability models based on empirical data. Different approaches are existing for such kind of models in the field of accident research. There is a need for harmonization in terms of the used methods and data as well as the handling with the existing challenges. These are preparation of the dataset, model assumptions, censored/unknown data, evaluation of model accuracy, definition of dependent and independent variable, and others. In the presented study, several empirical, statistical and phenomenological approaches were analyzed regarding their advantages and disadvantages and also their applicability. Furthermore, the identification of appropriate prediction parameters for the injury severity of pedestrians has been considered. Due to its main effect on injuries of pedestrians and bicyclists, the importance of the secondary impact has also been analyzed. Finally, the model accuracy, evaluated by several criteria, is the rating factor that gives the quality and reliability for application of the resulting models. After the investigation and evaluation of statistical approaches one method was chosen and appropriate prediction variables were examined. Finally, all findings were summarized and injury risk functions for pedestrians in real world accidents were created. Additionally, the paper gives instructions for the interpretation and usage of such functions. The presented results include IRFs for several injury severity levels and age groups. The presented models are based on a high amount of real world accidents and describe very well the injury severity probability of pedestrians and bicyclists in frontal collisions with current vehicles. The functions can serve as basis for the evaluation of effectiveness of systems like Pedestrian-AEB or Bicycle-AEB.
When assessing the consequences of accidents normally the injury severity and the damage costs are considered. The injury severity is either expressed within the police categories (slight injury, severe injury or fatal injury) or the AIS code that rates the fatality risk of a given injury. Both injury metrics are assessing the consequences of the accident directly after the accident. However, not all consequences of accidents are visible directly after the accident and the duration of the consequences are different. Besides a physiological reduction of functionality social and psychological implications such as reduced mobility options, problems to continue the original job etc. are happening. In order to assess long term consequences of accidents the MHH Accident Research Unit established a brief questionnaire that is distributed to accident involved people of the Hannover subset of the GIDAS data set approx. one year after the accident beginning with the accident year 2013. The basic idea of using a brief questionnaire (in fact only one page) is to obtain a relatively large return rate because the questionnaire appears to be simple and quickly answered. This appears to be important because it is believed that the majority of accident involved people will not report long term consequences. In order to allow a more detailed survey amongst those responders that are reporting long term consequences they are asked for a written consent for the additional questionnaire that will be distributed at a time that is not yet defined. Long term consequences are reported for all addressed areas, medical, physiological, psychological and sociological by people without injuries, with minor injuries and with severe injuries.
[Introduction:] A large number of road users involved in road traffic crashes recover from their injuries, but some of them never recover fully and suffer from some kind of permanent disability. In addition to loss of life or reduced quality of life, road accidents carry many and diverse consequences to the survivors such as legal implications, economic burden, job absences, need of care from a third person, home and vehicle adaptations as well as psychological consequences. Within an EU funded project MOVE/C4/SUB/2011-294/SI2.628846 (REHABIL AID) these consequences were analyzed more detailed.
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.
Whiplash injuries are characterized by the high variability of its symptoms and by the subjectivity of its diagnosis, which sometimes leads to frauds perpetrated by victims of rear-end impacts. It is estimated that whiplash injuries cost annually about 10.000 million Euros in Europe. Therefore, the aim of this study was to investigate the influence of the dynamics of the accident in which the victim was involved in the probability of development of whiplash associated injuries. In the presented methodology, first an accident reconstruction is performed where the dynamics of the accident is determined. This is carried out using the software PC-Crash, police and insurance companies' data. Then biomechanical injuries criteria related with whiplash injuries are evaluated. For the evaluation of the probability of having whiplash injuries, the Neck Injury Criterion (NIC) of the victim and the mean acceleration of the vehicle were evaluated. Then, with medical reports, the results of the accident reconstruction are correlated with the reported injuries. Some examples are presented. The results obtained indicate that the study of the dynamics of the road accidents in which the victims were involved could be used as an auxiliary of the prognosis of whiplash injuries and is important for a precise diagnosis of this type of injuries.
In most of developed countries, the progress made in passive safety during the last three decades allowed to drastically reduce the number of killed and severely injured especially for occupants of passenger cars. This reduction is mainly observed for frontal impacts for which the AIS3+ injuries has been reduced about 52% for drivers and 38% for front passengers. The stiffening of the cars' structure coupled with the generalization of airbags and the improvement of the seatbelt restraint (load limiter, pretension, etc.) allowed to protect vital body regions such as head, neck and thorax. However, the abdomen did not take advantage with so much success of this progress. The objective of this study is to draw up an inventory on the abdominal injuries of the belted car occupants involved in frontal impact, to present adapted counter-measures and to assess their potential effectiveness. In the first part the stakes corresponding to the abdominal injuries will be defined according to types of impact, seat location, occupants' age and type of injured organs. Then, we shall focus on the abdominal injury risk curves for adults involved in frontal impact and on the comparisons of the average risks according to the seat location. In the second part we will list counter-measures and we shall calculate their effectiveness. The method of case control will be used in order to estimate odds ratio, comparing two samples, given by occupants having or not having the studied safety system. For this study, two type of data sources are used: national road injured accident census and retrospective in-depth accident data collection. Abdominal injuries are mainly observed in frontal impact (52%). Fatal or severe abdominal occupant- injuries are observed at least in 27% of cases, ranking this body region as the most injured just after the thorax (51%). In spite of a twice lower occupation rate in the back seats compared to the front seats, the number of persons sustaining abdominal injuries at the rear place is higher than in the front place. In recent cars, the risk of having a serious or fatal abdominal injury in a frontal impact is 1.6% for the driver, 3.6% for the front passenger and 6.3% for the rear occupants. The most frequently hurt organs are the small intestine (17%), the spleen (16%) and the liver (13%). The most common countermeasures have a good efficiency in the reduction of the abdominal injuries for the adults: the stiffness of the structure of the seats allows decreasing the abdominal injury risk from 54% (driver) to 60% (front occupant), the seatbelt pretensioners decrease also this risk from 90% (driver) to 83% (front passenger).
Still correlated with high mortality rates in traffic accidents traumatic aortic ruptures were frequently detected in unprotected car occupants in the early years. This biomechanical analysis investigates the different kinds of injury mechanisms leading to traumatic aortic injuries in todays traffic accidents and how the way of traffic participation affects the frequency of those injuries over the years. Based on GIDAS reported traffic accidents from 1973 to 2014 are analyzed. Results show that traumatic aortic injuries are mainly observed in high-speed accidents with high body deceleration and direct load force to the chest. Mostly chest compression is responsible for the load direction to the cardiac vessels. The main observed load vector is from caudal-ventral and from ventral solely, but also force impact from left and right side and in roll-over events with chest compression lead to traumatic aortic injuries. Classically, the injury appeares at the junction between the well-fixed aortic arch and the pars decendens following a kind of a scoop mechanism, a few cases with a hyperflexion mechanism are also described. In our analysis the deceleration effect alone never led to an aortic rupture. Comparing the past 40 years aortic injuries shift from unprotected car occupants to today's unprotected vulnerable road users like pedestrians, cyclists and motorcyclists. Still the accident characteristics are linked with chest compression force under high speed impact, no seatbelt and direct body impact.
To elucidate the risk of pedestrians, bicycle and motorbike users, data of two accident research units from 1999 to 2014 were analysed in regard to demographic data, collision details, preclinical and clinical data using SPSS. 14.295 injured vulnerable road users were included. 92 out of 3610 pedestrians ("P", 2.5%), 90 out of 8307 bicyclists ("B", 1.1%) and 115 out of 4094 motorcycle users ("M", 2.8%) were diagnosed with spinal fractures. Thoracic fractures were most frequent ahead of lumbar and cervical fractures. Car collisions were most frequent mechanism (68, 62 and 36%). MAIS was 3.8, 2.8 and 3.2 for P, B and A with ISS 32, 16 and 23. AIS-head was 2.2, 1.3 and 1.5). Vulnerable road users are at significant risk for spine fractures. These are often associated with severe additional injuries, e.g. the head and a very high overall trauma severity (polytrauma).