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Validation of human pedestrian models using laboratory data as well as accident reconstruction
(2007)
Human pedestrian models have been developed and improved continually. This paper shows the latest stage in development and validation of the multibody pedestrian model released with MADYMO. The biofidelity of the multibody pedestrian model has been verified using a range of full pedestrian-vehicle impact tests with a large range in body sizes (16 male, 2 female, standing height 160-192cm, weight 53.5-90kg). The simulation results were objectively correlated to experimental data. Overall, the model predicted the measured response well. In particular the head impact locations were accurately predicted, indicated by global correlation scores over 90%. The correlation score for the bumper forces and accelerations of various body parts was lower (47-64%), which was largely attributed to the limited information available on the vehicle contact characteristics (stiffness, damping, deformation). Also, the effects of the large range in published leg fracture tolerances on the predicted risk to leg fracture by the pedestrian model were evaluated and compared with experimental results. The validated mid-size male model was scaled to a range of body sizes, including children and a female. Typical applications for the pedestrian models are trend studies to evaluate vehicle front ends and accident reconstructions. Results obtained in several studies show that the pedestrian models match pedestrian throw distances and impact locations observed in real accidents. Larger sets of well documented cases can be used to further validate the models especially for specific populations as for instance children. In addition, these cases will be needed to evaluate the injury predictive capability of human models. Ongoing developments include a so-called facet pedestrian model with a more accurate geometry description and a more humanlike spine and neck and a full FE model allowing more detailed injury analysis.
The project UR:BAN "Cognitive assistance (KA)" aims at developing future assistance systems providing improved performance in complex city traffic. New state-of-the-art panoramic sensor technologies now allow comprehensive monitoring and evaluation of the vehicle environment. In order to improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is the evaluation and prediction of their behaviour and actions. The objective of subproject "WER" is development support by providing quantitative estimates of traffic collisions at the very start and predict potential in terms of optimized accident avoidance and reduction of injury severity. For this purpose an integrated computer simulation toolkit is being devised based on real world accidents (GIDAS as well as video documented accidents), allowing the prediction of potential effectiveness and future benefit of assistance systems in this accident scenario. Subsequently, this toolkit may be used for optimizing the design of implemented assistance systems for improved effectiveness.
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.
In road traffic accidents, a car-seat and its occupant can be subjected to various crash pulses in the case of a rear impact. This study investigates the influence of crash pulse shape on seat-occupant response and evaluates the corresponding risk of whiplash injury. For this purpose, a rigorously validated seat-occupant system model is used to study different carseat designs and crash pulses. Two different car-seat concepts are also presented which can effectively mitigate whiplash injury for a wide range of crash severity. It is shown that for crash pulses of similar severity, the level of whiplash-risk depends strongly on the combined effects of seat design and crash pulse shape.
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.
This study is aimed to investigate the correlations of impact conditions and dynamic responses with the injuries and injury severity of child pedestrians by accident reconstruction. For this purpose, the pedestrian accident cases were selected from Sweden and Germany with detailed information about injuries, accident cars, and accident environment. The selected accident cases were reconstructed using mathematical models of pedestrian and passenger car. The pedestrian models were generated based on the height, weight, and age of the pedestrian involved in accidents. The car models were built up based on the corresponding accident car. The impact speeds in simulations were defined based on the reported data. The calculated physical quantities were analyzed to find the correlation with injury outcomes registered in the accident database. The reconstruction approaches are discussed in terms of data collection, estimating vehicle impact speeds, pedestrian moving speeds and initial posture, secondary ground impact, validity of the mathematical models, as well as impact biomechanics.
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.
Fire incidents are among the most relevant for people in a tunnel. Therefore, it is important to be sufficiently prepared for such events. A large scale fire test is to be used to help evaluate the initial burning duration and the time it takes for the fire to spread to other vehicles in the tunnel, and in particular how long it takes for a truck carrying wooden pallets to catch fire, taking into consideration the extremely high temperatures. The goal, therefore, is to determine the time it takes for a fire to spread to other vehicles in the tunnel. In the large scale fire test, an accident in a tunnel with one-way traffic is simulated between a truck loaded with approximately 3.7 t of wooden Europol pallets and a passenger car. Directly behind each of the vehicles involved in the accident there is another car which stops at a distance of 1.0 m. Approximately 300 litres of burning diesel are discharged from the truck's fuel tank, which is simulated by using approximately 400 litres of isopropanol. A 10 m-² burning pool forms underneath the truck. Other objectives of the large scale fire test are the validation of the CFD models and the evaluation of the progression of the thermal release ratios estimated for the simulation. The thermal release ratios generated in the test are determined and evaluated using various models.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
The Swedish National Road Administration (SNRA), the Japanese Automobile Research Institute (JARI) and the Federal Highway Research Institute (BASt) are co-operating in the International Harmonized Research Activities on Intelligent Transportation Systems (IHRA-ITS). Under this umbrella a joint study was conducted. The overall objective of this study was to contribute to the definition and validation of a "battery of tools" which enables a prediction and an assessment of changes in driver workload due to the use of in-vehicle information systems (IVIS) while driving. In this sense \"validation\" means to produce empirical evidence from which it can be concluded that these methods reliably discriminate between IVIS which differ in terms of relevant features of the HMI-design. Additionally these methods should also be sensitive to the task demands imposed on the driver by the traffic situation and their interactions with HMI-design. To achieve these goals experimental validation studies (on-road and in the simulator) were performed in Sweden, Germany and Japan. As a common element these studies focused on the secondary task methodology as an approach to the study of driver workload. In a joint German-Swedish on-road study the Peripheral Detection Task (PDT) was assessed with respect to its sensitivity to the complexity of traffic situations and effects of different types of navigation systems. Results show that the PDT performance of both the German and the Swedish subjects reflects the task demands of the traffic situations better than those of the IVIS. However, alternative explanations are possible which will be examined by further analyses. Results of this study are supplemented by the Japanese study where informational demands induced by various traffic situations were analysed by using a simple arithmetic task as a secondary task. Results of this study show that relatively large task demands can be expected even from simple traffic situations.