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Providing effective occupant protection in rollover crashes requires supplying the occupant with a restraint system proven effective in the dynamic rollover accident mode. Preventing ejection and providing restraint sufficient to prevent potentially injurious contacts with both interior and exterior vehicle components is paramount for effective rollover occupant protection. Research has shown that the injury potential can be decreased by closely coupling the occupant to the seat. This paper focuses on the effect of restraint system slack and its relationship to occupant excursion and ejection potential during rollover. Various restraint system configurations are evaluated in rollover-type test environments. A review of prior research is presented prior to presenting new quasi-static vehicle inversion studies conducted with live surrogate occupants. Additionally, dynamic rollover testing utilizing anthropometric test devices (ATDs) is presented. The influence of belt looseness and effects of various restraint designs on the belted occupants' injury potential are discussed.
The need of passive safety devices, able to reduce the accidents and the severity of injuries suffered by motorcyclist, distinctly arises from data on accident statistics. In this paper, the effectiveness of an airbag device fitted in the biker- garments has been verified through various numerical simulations. Two simple test conditions were defined, in order to investigate the performance of the device both for back and front impacts, and simulated at various impact speeds. With the aim of providing more information about the actual capability of the airbag to reduce the severity of the injuries, one of accident scenario described by ISO 13232:2005 has been also investigated, checking the real effectiveness of the airbag strap-based firing system too. Confrontation of injury indexes resulting from simulation with and without airbag made possible a realistic evaluation of the harm reduction induced by the airbag presence.
In order to enable foreseeing or comparing the benefit of safety systems or driver assistance systems in Germany, in the United States and in Japan, the traffic accident databases in those three countries are examined. The variables used are culpable party, collision partner, accident type, and injury level and the method to re-classify the databases for comparison are proposed. The result indicates that single passenger car fatality is the most frequent in Germany and in the United States, while passenger car vs. pedestrian is the most frequent fatality scenario in Japan. When the casualty by fatality ratio is focused, the greatest difference is observed in rear-end collisions. The ratio of slight injuries in Japan yields about eighteen times as many as those in Germany, and about eight times as many as those in the United States.
Accident data shows that the vast majority of pedestrian accidents involve a passenger car. A refined method for estimating the potential effectiveness of a technology designed to support the car driver in mitigating or avoiding pedestrian accidents is presented. The basis of the benefit prediction method consists of accident scenario information for pedestrian-passenger car accidents from GIDAS, including vehicle and pedestrian velocities. These real world pedestrian accidents were first reconstructed and the system effectiveness was determined by comparing injury outcome with and without the functionality enabled for each accident. The predictions from Volvo Cars" general Benefit Estimation Model are refined by including the actual system algorithm and sensing models for a relevant car in the simulation environment. The feasibility of the method is proven by a case study on a authentic technology; the Auto Brake functionality in Collision Warning with Full Auto Brake and Pedestrian Detection (CWAB-PD). Assuming the system is adopted by all vehicles, the Case Study indicates a 24% reduction in pedestrian fatalities for crashes where the pedestrians were struck by the front of a passenger car.
An eCall device has been mounted on some vehicles in France since 2003. It is an integrated car radio/GSM/GPS system that can be used with a SIM card. When an accident occurs, a call can be sent manually or automatically made to a telephone call centre. Knowing the geographic location, the vehicle identity and the possibility of a direct communication with the people involved enables the nearest emergency services to be called out. In this context, the LAB / CEESAR have set up a study aimed at evaluating the effectiveness of this system. The purpose of this paper is to detail the E-call system evaluation method of effectiveness used and give a global synthesis of the results.
Females sustain Cervical Spine Distortion injury (CSD) more often than males. Most work dealing with the biomechanics background (e.g. injury mechanism/criteria) as well as the application in seat design/testing, focuses on the occupant model of an average male. Therefore the EU-Project ADSEAT (Adaptive Seat to Reduce Neck Injuries for Female and Male Occupants) is aimed at adding a female model for gender balanced research of CSD and improving seat design. An extensive literature review, searching for risk factors and injury criteria for males and females, was accompanied by the evaluation of different databases containing CSD cases. The database evaluations suggests that an anthropometry quite close to the 50%ile female anthropometry as known from crash test dummy design is appropriate. The results presented here form the basis for the future development of a computational female model and the improvement of seat design for better protection of both males and females in the frame of the ADSEAT-Project.
It has been pointed that most of the accidents on the roads are caused by driver faults, inattention and low performance. Therefore, future active safety systems are required to be aware of the driver status to be able to have preventative features. This probe study gives a system structure depending on multi-channel signal processing for three modules: Driver Identification, Route Recognition and Distraction Detection. The novelty lies in personalizing the route recognition and distraction detection systems according to particular driver with the help of driver identification system. The driver ID system also uses multiple modalities to verify the identity of the driver; therefore it can be applied to future smart cars working as car-keys. All the modules are tested using a separate data batch from the training sets using eight drivers" multi-channel driving signals, video and audio. The system was able to identify the driver with 100% accuracy using speech signals of length 30 sec or more and a frontal face image. After identifying the driver, the maneuver/ route recognition was achieved with 100% accuracy and the distraction detection had 72% accuracy in worst case. In overall, system is able to identify the driver, recognize the maneuver being performed at a particular time and able to detect driver distraction with reasonable accuracy.
The aim of this study was to evaluate the performance and accuracy of Event Data Recorders (EDRs). The analysis was based on J-NCAP crash tests from 2006"2007, with the corresponding EDR datasets. The pre-crash velocity, maximum delta-V and delta-V versus time history data recorded in the EDRs were compared with the reliable crash test data. The difference between the EDR pre-crash velocity and the laboratory test speed was less than 4 percent. In contrast, in several cases the maximum delta-V and delta-V versus time history data obtained from the EDRs showed uncertainty of measurement in comparisons with the reliable delta-V data. The difference in maximum delta-V in these comparisons was more than 5 percent in 10 of 14 tests and more than 10 percent in 4 of 14 tests. The EDRs underestimated the maximum delta-V in almost all tests. It was also concluded that the calculated acceleration from the EDR delta-V versus time history data showed good agreement with the instrumented accelerometer signal during the collision in almost all tests.
Impact severity is a fundamental measure for all in-depth crash investigation projects. One methodology used in the UK is based on the US Calspan software package CRASH3. The UK- in-depth crash investigation studies routinely use AiDamage3 a software package which is based on an updated version of the original CRASH3 algorithm, including enhancements to the vehicle stiffness coefficients. Real world accident-damaged vehicles are measured and their crush is correlated with a library of stiffness coefficients. These measurements are then used, along with other parameters, to calculate the crash energy and equivalent changes of velocity of the vehicles (delta-v), which is a measure of the impact severity. UK in-depth accident studies routinely validate the crash severity methodologies applied as the vehicle fleet changes. This is achieved by analysing crash test data and using the appropriate residual crush damage and other inputs to AiDamage3 and checking the program- outputs with the known crash severity parameters. This procedure checks, at least in part, the default stiffness values in the data libraries and the reconstruction methods used.
The focus of the technical innovation in the automobile industry is currently changing to sensor based safety systems, which are operating in the pre-crash phase of an accident. To get more information about this pre-crash phase for real accidents a simulation of this phase using the GIDAS database is done. The basics for this simulation are geometrical information about the accident location and the exact accident data out of the GIDAS database. This aggregated information gives the possibility to simulate an exact motion for every accident participant, using MATLAB / SIMULINK, in the pre-crash phase. After the simulation the information about the geometrical positions, the velocities and maneuvers of the drivers to an individual TTC (time to collision) are available. With those results it is possible to develop new useful sensor geometries using pre-crash scatter plots or estimate the efficiency of implemented active safety systems in combination with sensor characteristics. This simulation can be done for every reconstructed accident included in the GIDAS database, so these results can represent a wide spread basis for the further development of active safety systems and sensor geometries and characteristics