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In 2014 the sixth ESAR conference (Expert Symposium on Accident Research) was held in Hannover. ESAR is an international convention of experts, who analyze traffic accidents all over the world and discuss their results in this context, conducted at the Medizinische Hochschule Hannover every 2 years. It connected representatives of public authorities, engineers in automotive development and scientists and offers a forum with particular emphasis on In-Depth-Analyses of accident statistics and accident analyses. Special focus is placed on research on the basis of so-called "In-Depth-Accident-Investigations" [data collections at the sites of the accidents], which are characterized by extensive documentations of the sites of the accidents, of the vehicles as well as of the injuries, encompassing several scientific fields. ESAR aims at a multi-disciplinary compilation of scientific results and at discussing them on an international, scientific level. It is thus a scientific colloquium and a platform for exchanging information for all accident researchers. Experiences in accident prevention as well as in the complex field of accident reconstruction are stated and new research fields are added. Existing results of long-term research work in Europe, the US, Australia and Japan include different infrastructural correlations and give findings on population, vehicle population and driver characteristics, which offer a basis for recommendations to be derived and measures for increasing road safety.
A methodology to derive precision requirements for automatic emergency braking (AEB) test procedures
(2015)
AEB Systems are becoming important to increase traffic safety. Test procedures in testing for consumer information, manufacturer self-certification and technical regulations are used to ensure a certain minimum performance of these systems. Consequently, test robustness, test efficiency and finally test cost become increasingly important. The key driver for testing effort and test costs is the required repeatable accuracy in a test design - the higher the accuracy, the higher effort and test costs. On the other hand, the performance of active safety systems depends on time discretization in the environment perception and other sub-systems: for instance, typical sensors supply information with a cycle time of 50 - 150 ms. Time discretization results in an inherent spread of system performance, even if the test conditions are perfectly equal. The proposed paper shows a methodology to derive requirements for a test setup (e.g. test repeats, use of driving robots, ...) as function of AEB system generation and rating method (e.g. Euro NCAP points awarded, pass/fail, ...). While the methodology itself is applicable to AEB pedestrian and AEB Car-Car scenarios, due to the lack of sufficient test data for AEB Car-Car, the focus of this paper is on AEB pedestrian scenarios. A simulation model for the performance of AEB Pedestrian systems allows for the systematic variation of the discretization time as well as test condition accuracy. This model is calibrated with test results of 4 production vehicles for AEB Pedestrian, all fully tested by BASt according to current Euro NCAP test protocols. Selected parameters to observe the accuracy of the test setup in case of pedestrian AEB is the calculated impact position of pedestrian on the vehicle front (as if no braking would have occurred), and the test vehicle speed accuracy. These variable was shown in real tests to be repeatable in the range of ± 5 cm and ± 0,25 km/h, respectively, with a fully robotized state of the art test setup. The sensitivity of AEB performance (measured in achieved speed reduction as well as overall rating result according to current Euro NCAP rating methods) towards discretization and the sensitivity of performance towards test accuracy then is compared to identify economic yet robust test concepts. These comparisons show that the available repeatability accuracy of current test setups is more than sufficient for today's AEB system capabilities. Time discretization problems dominate the performance spread especially in test scenarios with a limited pedestrian dummy reveal time (e.g. child behind obstruction, running adult scenarios with low car speeds). This would allow to increase test tolerances to decrease test cost. A methodology which allows to derive the required tolerances in active safety tests might be valuable especially for NCAPs of emerging countries that do not have the necessary equipment (e.g. driving robots, positioning units) available for the full-scale and high tolerance EuroNCAP active safety procedures yet still want to rate active safety systems, thus improving the global safety.
Autonomous Emergency Braking (AEB) systems for pedestrians have been predicted to offer substantial benefit. On this basis, consumer rating programmes, e.g. Euro NCAP, are developing rating schemes to encourage fitment of these systems. One of the questions that needs to be answered to do this fully, is to determine how the assessment of the speed reduction offered by the AEB is integrated with the current assessment of the passive safety for mitigation of pedestrian injury. Ideally, this should be done on a benefit related basis. The objective of this research was to develop a benefit based methodology for assessment of integrated pedestrian protection systems with pre-crash braking and passive safety components. A methodology has been developed which calculates the cost of pedestrian injury expected, assuming all pedestrians in the target population (i.e. pedestrians impacted by the front of a passenger car) are impacted by the car being assessed, taking into account the impact speed reduction offered by the car’s AEB (if fitted) and the passive safety protection offered by the car’s frontal structure. For rating purposes, this cost can be normalised by comparing it to the cost calculated for selected cars. The methodology uses the speed reductions measured in AEB tests to determine the speed at which each casualty in the target population will be impacted. The injury to each casualty is then calculated using the results from standard Euro NCAP pedestrian impactor tests and injury risk curves. This injury is converted into cost using ‘Harm’ type costs for the body regions tested. These costs are weighted and summed. Weighting factors were determined using accident data from Germany and GB and the results of a benefit analysis performed by the EU FP7 AsPeCSS project. This resulted in German and GB versions of the methodology. The methodology was used to assess cars with good, average and poor Euro NCAP pedestrian ratings, with and without a current AEB system fitted. It was found that the decrease in casualty injury cost achieved by fitting an AEB system was approximately equivalent to that achieved by increasing the passive safety rating from poor to average. Also, it was found that the assessment was influenced strongly by the level of head protection offered in the scuttle and windscreen area because this is where head impact occurs for a large proportion of casualties. The major limitation within the methodology is the assumption used implicitly during weighting. This is that the cost of casualty injuries to body areas, such as the thorax, not assessed by the headform and legform impactors, and other casualty injuries such as those caused by ground impact, are related linearly to the cost of casualty injuries assessed by the impactors. A methodology for assessment of integrated pedestrian protection systems was developed. This methodology is of interest to consumer rating programmes which wish to include assessment of these systems. It also raises the interesting issue if the head impact test area should be weighted to reflect better real-world benefit.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
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.
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 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.
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.