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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.
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
Over the last decades the number of traffic accident fatalities on German roads decreased by 77% down to 4968 in the year 2007. This positive development is due to optimisations of vehicle safety, roads and infrastructure and medical rescue issues. Up to now mostly the optimisations of secondary safety measures lead to this effect on vehicle safety. Since some years more and more driver assistance systems are available and lead to a further reduction of all accidents. These new systems are often comfort systems and have not primarily been developed to increase vehicle safety. In contrast to secondary safety systems primary safety systems are able to mitigate and avoid accidents. So in the future it is important to estimate the benefit of these systems in reducing accident numbers as well. Current benefit estimation methods mostly focus on a single system only and not on the combination of systems. In this paper a new method for a multivariate benefit estimation based on real accident data is developed. The paper describes the basic method to estimate the benefit of primary and secondary safety systems in combination. With the presented method the benefit will not be overestimated as it would be by a simple addition of the benefits of single systems. The model will be validated by a multivariate prospective benefit estimation of different vehicle safety systems in comparison to single benefit estimations of the same systems. For this the German In-Depth Accident Database is used. The results show the importance to implement the interactions of safety systems in the estimation process and rate the overestimation by a simple addition of the single system benefits. The validation includes primary and secondary safety systems in combination. The validation is done using more than 3500 real accidents which were initiated by cars. This sample out of the GIDAS database is representative for the current accident situation in Germany. The paper shows the necessity of a multivariate estimation of the benefit for existing and future safety systems.
A set of recommendations for pan-European transparent and independent road accident investigations has been developed by the SafetyNet project. The aim of these recommendations is to pave the way for future EU scale accident investigation activities by setting out the necessary steps for establishing safety oriented road accident investigations in Member States. This can be seen as the start of the process for establishing road accident investigations throughout Europe which operate according to a common methodology. The recommendations propose a European Safety Oriented Road Accident Investigation Programme which sets out the procedures that need to be put in place to investigate a sample of every day road accidents. They address four sets of issues; institutional addressing the characteristics of the programme; operational describing the conditions under which data isrncollected; data storage and protection; and reports, countermeasures and the dissemination of data.rn