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For more than a decade, ADAC accident researchers have analysed road accidents with severe injuries, recording some 20,000 accidents. An important task in accident research is to determine the causative factors of road accidents. Apart from vehicle engineering and human factors, accident research also focuses on infrastructural and environmental aspects. To find out what accident scenarios are the most common in ADAC accident research and what driver assistance systems can prevent them, our first task was to conduct a detailed accident analysis. Using CarMaker, we performed a realistic simulation of accident scenarios, including crashes, with varying parameters. To begin with, we made an initial selection of driver assistance systems in order to determine those with the greatest accident prevention potential. One important finding of this study is that the safety potential of the individual driver assistance systems can actually be examined. It also turned out that active safety offers even much more potential for development and innovation than passive safety. At the same time, testing becomes more demanding, too, as new systems keep entering the market, many of them differing in functional details. ADAC will continue to test all driver assistance systems as realistically as possible so as to be able to provide advice to car buyers. Therefore, it will be essential to develop and improve test conditions and criteria.
The GIDAS-investigation team of Dresden (VUFO) has documented more than 11.500 accidents since 1999. The documentation of the accident includes beside vehicle-, injury- and environmental-data very detailed reconstruction data. Within this accident investigation the VUFO began to record the skid resistance of the accident site in 2009. The measurements are divided in macro- and microroughness (Sand depth method and Portable Skid Resistance Tester-SRT-by Munro-Stanley London-©). Both methods are used to determine the skid resistance for more than 1000 passenger cars. The aim of the present study is to find out a relationship between the measured skid resistance, the road conditions and the friction coefficient, which is used to calculate the maximum accelerations and decelerations during a reconstruction of an accident. Basic approach to convert the SRT-value into the friction coefficient is the calculation of the theoretical absorbed energy of the spring rubber system of the swinging arm of lever. This absorbed energy is used to get the friction coefficient by using the equations for the work of friction. To consider the road-behavior, in correlation to the friction coefficient, the results will be merged with existing literature. Last step for this study will be a comparison between actual used friction coefficients all over the GIDAS-database and the theoretical results. The study shows, if it is possible to use the SRT-Measurement for the estimation of a friction coefficient for the reconstruction of a traffic accident. As expected, the GIDAS-Database and the additional measurement of the roughness of the road directly on the spot are an enormous useful dataset.
In recent years the boundaries between active and passive safety blurred more and more. Passive safety in the traditional term includes all safety aspects to prevent occupants to be injured or at least injury severity should be reduced. Passive Safety starts with the collision (first vehicle contact) and ends with rescue (open vehicle doors). Within this phase the occupant has to be protected by the passenger compartment whereby no intrusion should occur. Active safety on the other side was developed to interact prior to the collision whereby the goal is to prevent accidents. The extensive interaction between active and passive safety led to the terminologies "Primary" and "Secondary" safety whereas the expression Integrated Safety Concept was generated. Within this study the most well documented single vehicle accidents with cars not equipped with ESP were identified from the PENDANT database and reconstructed. Additional cases were found in the database ZEDATU of TU Graz. In comparison each case was simulated with the assumption that the cars were equipped with ESP. The differences regarding accident avoidance or crash severity as well as reduction of injury risk were analysed.
Cycle helmets have continued to increase in popularity since their introduction half a century ago. Many studies indicate that overall, head injury can be significantly reduced by wearing them. This study was conducted using two distinct sets of real-world cycling collision data from Ireland, namely cases involving police collision reports and cases involving admission to a hospital emergency department. The analyses sought to simulate and analyse the protective performance of cycle helmets in such collision scenarios, by comparing the Head Injury Criterion score and peak head accelerations, both linear and angular. Cycle collisions were simulated using the specialised commercial software MADYMO. From the simulation results, these key metrics were compared between the same-scenario helmeted and unhelmeted cyclist models. Results showed that the inclusion of bicycle helmets reduced linear accelerations very significantly, but also increased angular accelerations significantly compared to unhelmeted situations. Given the modest protective performance of cycle helmets against angular accelerations, it is recommended that cycle helmet manufacturers and international test standards need to pay more attention to head angular accelerations.
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.
Event Data Recorder (EDR) is an additional function installed in airbag control module (ACM) to record vehicle and occupant information for a brief period of time before, during, and after a crash event. EDRs are now being installed in ACMs by several automakers in the USA and in Japan. The aim of this study is to understand the performance of EDRs for the improvement of accident reconstruction with more reliable information. In the first report of the study, data obtained from EDRs of seven vehicle types were evaluated using 2006-2007 J-NCAP (Japanese new car assessment program) full-lap frontal barrier crash tests and offset frontal deformable barrier crash tests data. For more practical standpoint, we conducted thirteen crash tests reconstructing typical real-world accidents such as single vehicle accidents with barriers or poles, car to car accidents and multi rear-end collisions focusing on Japanese typical accident types. Data obtained from EDRs are compared with data obtained from optical speed sensor, instrumented accelerometers and high speed video cameras. The velocities determined from pre-crash data of EDRs and the maximum change in velocity, delta-V, and delta-V time history data obtained from post-crash data of EDRs are analyzed. The results are as follows: - Pre-crash velocities of EDRs were very accurate and reliable. An average difference between the EDR recording values and reference speeds was 4.2% and a root mean square of the differences was 9.2%. Only two cases resulted large differences for the pre-crash velocity. Both of them were cases with braking prior to the collision. However, another test with braking resulted less difference. The braking condition may influence accuracy of pre-crash velocities. - Maximum delta-Vs obtained from the EDRs showed uncertainty of measurement in several cases in comparisons with the reliable delta-V data. The differences in maximum delta-V were more than 10% in five of twenty-five events data and more than 20% in two of twenty-five events data. An average of the all differences was about 4% and root mean square of the differences was about 11%. Especially large deformation at narrow area may influence accuracy of post-crash delta-V. - Multiple rear-end crash tests were reconstructed using EDRs data as case studies. Some EDRs recorded two events and a time gap between two events, so that these reconstruction case studies were very accurate and reliable. - If though only one of three vehicles in multiple rear end crash was equipped EDR, overview and velocities of all cars may be reconstructed using these limited EDR data. In this case study, leading car- EDR data and middle car- EDR data were valuable. However if only following car was equipped EDR, the reconstruction was not accurate
Enhanced protection of pedestrians and cyclists remains on the focus. Besides infrastructural and behavioral aspects it is necessary to exploit technical solutions placed on motorized vehicles. Accident research needs reliable data as well as national road accident statistics. Changing the view on seriously injured road users is one of the challenges which will substantially contribute to the optimization on future traffic safety. The missing accuracy in the definition of personal injury has a detrimental effect on making cost efficient road safety policy which is not only focused on fatal accidents. The European commission requested that, starting in 2015, all EU member states provide more detailed data on the injury status of road casualties, with special regard to the group of seriously injured. Conventional accident data will always be essential. But to obtain detailed data about driver behavior in real traffic situations further data sources are required. These could be EDR data, data from electronic control units, data from traffic surveys and traffic counting, naturalistic diving studies and field operational tests. Gaining insight into normal as well as critical driver behavior will enable accident researchers to deduct functions estimating the increase or decrease of accident risk associated with certain behaviors or vehicle functions. Also with view to the introduction of highly automated driving functions in the future such data is urgently needed. Computer simulation based tools to estimate the benefits of active safety systems are another step on the way towards the safety assessment of automated driving. It is now the duty of the scientific community to ask the right questions, to develop a methodology and to merge all these data sources into a common framework for the assessment of future traffic safety innovations.
Small overlap frontal crashes are defined by a damage pattern with most of the vehicle deformation concentrated outboard of the main longitudinal structures. These crashes are prominent among frontal crashes resulting in serious and fatal injuries, even among vehicles that perform well in regulatory and consumer information crash tests. One of the critical aspects of understanding these crashes is knowing the crash speeds that cause the types of damage associated with serious injuries. Laboratory crash tests were conducted using 12 vehicles in three small overlap test conditions: pole, vehicle-to-vehicle collinear, and vehicle-to-vehicle oblique (15-degree striking angle). Field reconstruction techniques were used to estimate the delta V for each vehicle, and these results were compared with actual delta V values based on vehicle accelerometer data. Estimated delta Vs were 50% lower than actual values. Velocity change estimates for small overlap frontal crashes in databases such as NASS-CDS significantly underestimate actual values.
Detailed investigations and reconstructions of real accidents involving vulnerable road users
(2005)
The aim of this research is to improve knowledge about vulnerable road users accidents and more specifically pedestrians or cyclists. This work has been based on a complete analysis of real accidents. From accidents chosen from an in-depth multidisciplinary investigation (psychology, technical, medical), we have tried to identify the configuration of the impact: car speed, pedestrian or cyclist orientations. Then, we have made a numerical modelling of the same configuration with a multibody software. In particular, we have reproduced the anthropometry of the victim and the front shape of the car. A first simulation has been performed on this starting configuration. Next, effects of some parameters such as car velocity or victim position at impact have been numerically studied in order to find the best correlations with all indications produced by the in-depth analysis. Finally, the retained configuration was close to the presumed real accident conditions because it reproduces in particular the same impact points on the car, the same injuries, and is according to the driver statement. This double approach associating an in-depth accident analysis and a numerical simulation has been applied on pedestrian-to-car and bicyclist-tocar accidents. It has allowed us to better understand the real kinematics of such impacts. Even if this method is based on a case to case study, it underlines which parameters are relevant on a vulnerable road user accident investigation and reconstruction.
Real world accident reconstruction with the Total Human Model for Safety (THUMS) in Pam-Crash
(2013)
Further improvement of vehicle safety needs detailed analysis of real world accidents. According to GIDAS (German In-Depth Accident Study) most car to car front accidents occur at mid-crash severity. In this range thoracic injuries already occur. In this study a real world frontal crash with mid-crash severity out of the AARU database was reconstructed. The selected car to car accident was reconstructed by AARU by means of pc-crash software in order to get the initial dynamic accident conditions. These initial conditions were used to reconstruct the complete accident in more detail using FE models for the car structure and the occupants. Occupant simulations were performed with FE HIII-dummy models and the THUMS using Pam-Crash code. An initial THUMS validation was performed in order to verify the model-´s biofidelity by means of table-top test simulations. THUMS bone stiffness values were modified to match the real word occupant age. A comparison between driver and passenger restraint system loading was done, as well as an injury prediction comparison between the HIII-dummy model and THUMS response for both cases. Detailed comparison between the HIII-dummy models and THUMS regarding thoracic loading are discussed.
Neue Herausforderungen an die Unfallforschung durch Fahrerassistenz und automatisiertes Fahren
(2019)
Unfallrekonstruktion hat die Ableitung von Maßnahmen zur Minimierung der Unfallfolgen ermöglicht, vor allem durch Verbesserungen bei passiven Sicherheitseinrichtungen, aber auch durch die Verbesserung der Rettungskette, beispielsweise eCall. Heute können aktive Sicherheitssysteme die Unfallfolgen bereits vor der eigentlichen Kollision reduzieren oder durch Umfeldwahrnehmung und mittels Eingriff in die Fahrzeugsteuerung gegebenenfalls sogar vollständig verhindern. Funktionen, die aktiv in die Fahrzeugsteuerung eingreifen, lassen sich nach ihrer Wirkweise unterscheiden: zum einen handelt es sich um kontinuierlich automatisierende Funktionen, die meist länger aktiv bleiben (zum Beispiel ACC). Zum anderen um Funktionen, die in kritischen Fahrsituationen temporär in die Fahrzeugsteuerung eingreifen. Aufgezeigt wird, welche Konsequenzen und Risiken in Bezug auf diese Systeme sowie für bestimmte (zum Beispiel kritikale) Fahrsituationen anzunehmen sind. Zur Bewertung von aktiven Reglern, die in kritischen Fahrsituationen eingreifen, sind Unfalldaten nur noch eingeschränkt tauglich. Ähnliches gilt für die Bewertung von Ereignissen/ Zuständen im Rahmen kontinuierlicher Fahrzeugsteuerung, vor allem, wenn diese weiter vorausliegen. Wirkzusammenhänge automatisierter Fahrfunktionen müssen jedoch - gerade für den Mischverkehr mit konventionell gesteuerten Fahrzeugen - identifiziert werden. Dafür wird eine Szenariendatenbank mit relevanten Verkehrssituationen benötigt, in die Daten aus Naturalistic Driving Studies (NDS), aus Fahrversuchen oder Versuchen im Fahrsimulator eingehen können. Die zunehmende Durchdringung der Fahrzeugflotte mit kontinuierlich automatisierten Fahrfunktionen lässt eine Abnahme kritischer Fahrsituationen und eine Reduktion der Zahl der Verkehrsopfer erwarten. Allerdings verbleibt eine Restzahl an systemimmanenten Unfällen, die als unvermeidbar gelten müssen.
Since its creation in 2011 the Pre-Crash-Matrix (PCM) offers the possibility to observe the pre-crash phase until five seconds before crash for a wide range of accidents. Currently the PCM contains more than 8.000 reconstructed accidents out of the GIDAS (German In-Depth Accident Study) database and is enlarged continuously by more than 1.000 cases per year. Hence, a detailed investigation of active safety systems in real accident situations has been made feasible. The PCM contains all relevant data in database format to simulate the pre-crash phase until the first collision of the accident for a maximum of two participants. This includes the definition of the participants and their characteristics, the dynamic behavior of the participants as time-dependent course for five seconds before crash as well as the geometry of the traffic infrastructure. The digital sketch of the accident and information from GIDAS as well as from supplementary databases represent the main input for the simulation of the pre-crash phase of an accident with the VUFO simulation model VAST (Vufo Accident Simulation Tool). This simulation in turn embodies the foundation of the PCM. The PCM underlies continual improvements and enhancements in consultation with its users. In addition to collisions of cars with other cars, pedestrians, bicycles and motorcycles the PCM now also covers car to object and car to truck collisions. The paper illustrates car to truck collisions as a showcase and explains perspectives for further developments. In 2016 a more detailed definition of the contour of the vehicle was added. Furthermore, the geometrical surroundings of the accident site will be provided in a new structure with a higher level of detail. Thus, a precise classification of road marks and objects is possible to further improve the support of developing and evaluating ADAS. This paper gives an overview about the latest developments of the PCM with its innovations and provides an outlook to upcoming enhancements. Besides potential areas of application for the development of ADAS are shown.
The sequence of accident events can be classified by three essential phases, the pre-crash-sequence, the crash-sequence and the post-crash-sequence. The level of reliability of the information in the GIDAS-database (German In Depth Accident Study) is provided predominantly on the passive side. The period to evaluate active safety systems begins already in the pre-crash-sequence. The assessment of the potential of sensor- or communication-based active safety systems can only be accomplished by a detailed analysis of the pre-crash-phase. Hence the necessity to analyze the early period of the accident event in detail arises. This is possible with the help of the digital sketches of the accident site and the simulation of the accident by a simulation method of the VUFO GmbH. After simulating the pre-crash scenario it is possible to generate additional and standardized data to describe the pre-crash-sequences of an accident in a very high detail. These data are documented in a second database called the GIDAS Pre-Crash-Matrix (PCM). The PCM contains various tables with all relevant data to reproduce the pre-crash-sequence of traffic accidents from the GIDAS database until 5 seconds before the first collision. This includes parameters to describe the environment data, participant data and motion or dynamic data. This paper explains the creation of the PCM, the simulation itself and the contents and structure of the PCM. With this information of the pre-crash-sequence for various accident scenarios an improved benefit estimation and development of active safety systems can be made possible.
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.
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.
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.
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.