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Interdisciplinary accident research and research projects of AARU Audi Accident Research Unit
(2017)
AARU (Audi Accident Research Unit) is an interdisciplinary research project of the University Hospital Regensburg in cooperation with AUDI AG. Specific objective is to comprehend the respective accident scenario and retrieve generally applicable findings as to technical, medical and psychological processes. In order to prevent traffic accidents and to alleviate vehicle accident consequences, postulates of general traffic safety, human-machine interaction, technical design and function of new vehicles and occupant as well as third party protection shall be inferred from these findings. Specifically, each accident with new Audi, Lamborghini and Ducati vehicles involved is analyzed interdisciplinary, discussed in a case meeting and anonymously documented with more than 2,000 parameters. The database is continually used for solving safety relevant issues. Parallel to accident analysis, research projects are performed in the fields medicine, psychology and engineering in order to gain comprehensive insight and identify potential additional areas of activity of accident research.
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.
A lot of factors are related to a road traffic accident; particularly human factors such as road use characteristic, driving maneuver characteristic and safety attitude are the major ones. As a random factor is also included, so it is necessary to minimize the contribution of a random factor to identify human factors related to a road traffic accident. There are several standpoints for traffic accident analysis, such as vehicle-based, location-based and driver-based. And it is effective to analyze driver-based traffic accident data for discussion on the relation between human factors and accidents. An integrated traffic accident database system was developed for analysis considering driver- accident and violation records by ITARD, and several studies were carried out for the evaluation. Useful data for discussion on the relation between types of collision and traffic violations, and the effect of accident experience to the following accident were obtained.
A national initiative from the vehicle manufacturers, safety system suppliers, the road administration and universities in Sweden took off in 2007. The aim was to develop a national investigation network and a methodology focusing on all phases of a crash (pre-crash, in-crash and post-crash) as well as all parts of the road transport system (road user, vehicle and road environment). The initiative is formally run as a project with the acronym INTACT (Investigation Network and Accident Collection Techniques). It was a three year pilot with the aim to develop methodologies for an extended national crash investigation activity. During the first year the INTACT partners agreed on the aim for the investigation and methods for retrieving the data were developed. During the second and third year the methodology was tested in real-world investigations and further refinement was made. The paper describes the methodology developed to obtain high qualitative in-depth road crash data.
Injury severity of e.g. pedestrians or bikers after crashes with cars that are reversing is almost unknown. However, crash victims of these injuries can frequently be seen in emergency departments and account for a large amount of patients every year. The objective of this study is to analyze injury severity of patients that were crashed into by reversing cars. The Hannover Medical School local accident research unit prospectively documented 43,000 road traffic accidents including 234 crashes involving reversing cars. Injury severity including the abbreviated injury scale (AIS) and the maximum abbreviated injury scale (MAIS) was analyzed as well as the location of the accident. As a result 234 accidents were included into this study. Pedestrians were injured in 141 crashes followed by 70 accidents involving bikers. The mean age of all crash victims was 57 -± 23 years. Most injuries took place on straight stretches (n = 81) as well as parking areas (n = 59), entries (n = 36) or crossroads (n = 24). The AIS of the lower extremities was highest followed by the upper extremities. The AIS of the neck was lowest. The mean MAIS was 1.3 -± 0.6. The paper concludes that the lower extremities show the highest risk to become injured during accidents with reversing cars. However, the risk of severe injuries is likely low.
Recently, EuroNCAP updated the upper legform test protocols. The main objective of this study is to establish the upper legform test in KIDAS (Korean In-depth Accident Study) taking into account domestic pedestrian accident data as well as anthropometric data to protect elderly pedestrians whose average height and weight is much smaller and lighter than other age groups, especially compared to Europeans. Therefore 230 cases of pedestrian accidents from KIDAS were investigated to explore the injury severity of body regions as well as age related injury patterns. Injuries of all body regions were examined, with a special focus on injuries of abdomen and pelvic area. On the other hand, in order to explore Korea's pedestrian accident environment, national police data and KIDAS (Korean In-depth Accident Study) data were compared. The results should be taken into account in future analyses and possible improvements, such as regulations and KNCAP test protocols, of the pedestrian safety policy in Korea.
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.
Nowadays, traffic accidents are recorded in historical databases. Regarding the huge quantity of data, the use of data mining tools is essential to help Experts, for automatically extracting relevant information in order to establish and quantify relations between severity and potential factors of accidents. An innovative approach is here proposed for an in depth investigation of real world accidents data base. Mutual information ratio based on conditional entropies is used to quantity the association strength between an accident outcome descriptor (injury severity) and other potential association factors. Information theoretic methods help to select automatically groups of factors mostly responsible of the severity of accident.
This work describes the results of the experimental activity, illustrating the driving behavior observed in different conditions, relating them to the different methods of ADAS intervention and comparing the driver behavior without ADAS. In the present study, driver behavior was studied in road accidents involving elderly pedestrians, with different ADAS HMIs, as a base to develop a driver model in near missing pedestrian accidents. A literature research was conducted with the aim of finding out the main influencing factors, including environment, boundary conditions, configuration of impact, pedestrian and driver information, when pedestrian fatalities occur and an analysis of frequent road accidents was conducted to get more detailed information about the driver- behavior. In order to obtain more detailed information about pedestrian accidents, real road accidents were reconstructed with multibody simulations on PC-Crash and, by the comparison between literature findings and reconstructions, a generic accident scenario was defined. The generic accident scenario was implemented on the full scale dynamic driving simulator in use at the Laboratory for Safety and Traffic Accident Analysis (LaSIS, University of Florence, Italy) in order to analyse the driving behaviors of volunteers, also considering the influence of ADAS devices. Forty-five young volunteers were enrolled for this study, resulting in forty valid tests on different testing scenarios. Two different scenarios consisted in driving with or without ADAS in the vehicle. Different kinds of ADAS, acoustic and optical, with different time of intervention were tested in order to study the different reactions of the driver. The tests showed some interesting differences between driver's behavior when approaching the critical situation. Drivers with ADAS reacted earlier, but more slowly, depending also on the type of alarm, and often with double reaction when braking. In fact, the results of the activity showed that with ADAS intervention the time to collision (TTC) increases, but the reaction time and braking modality change: a) there is a sort of "latency" time between the accelerator pedal release and the brake pressure; b) the brake pressure is initially less intense. So the driver only partially takes advance from the TTC increase. These differences were valued not only qualitatively, but quantitatively as well. This work revealed to be useful to improve the knowledge of drivers" behavior, in order to realize a driver model that can be implemented to help attaining and assessing higher levels of automation through new technology.
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.