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The presentation deals with the simulation tool rateEFFECT which intends to answer the following questions: Which active safety systems should be developed to maximize safety benefit in real traffic accidents? What is the effectiveness of a specific active safety system in the real world? How many casualties could be avoided by such a system? It is shown that a lot of information is required to simulate existing accidents in order to estimate ADAS effects. This particularly includes numerical values for the pre-crash and in-crash phase. The database GIDAS provides a required minimum number of these parameters for a statistically significant sample.
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).
Rear-end collisions are the most frequent same and opposite-direction crashes. Common causes include momentary inattention, inadequate speed or inadequate distance. While most rear-end collisions in urban traffic only result in vehicle damage or slight injuries, rear-end collisions outside built-up areas or on motorways usually cause fatal or serious injuries. Driver assistance systems that detect dangerous situations in the longitudinal vehicle direction are therefore an essential safety plus. In view of this, for ADAC, systems that alert drivers to dangerous situations and initiate autonomous braking complement ESC as one of the most important active safety features in modern vehicles. The aim of ADAC is to provide consumers with technical advice and competent information about the systems available on the market. Reliable comparative tests that are based on standardised test criteria may provide motorists with important information and help them make a buying decision. In addition, they raise consumer awareness of the systems and speed up their market penetration. The assessment must focus on as many aspects of effectiveness as possible and include not only autonomous braking but also collision warning and autonomous brake assist. The work of the ADAC accident research is the development of the testing scenarios with direct link to accident situations and the identification of useful test criteria for testing.
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.
PROSPECT (Proactive Safety for Pedestrians and Cyclists) is a collaborative research project involving most of the relevant partners from the automotive industry (including important active safety vehicle manufacturers and tier-1 suppliers) as well as academia and independent test labs, funded by the European Commission in the Horizon 2020 research program. PROSPECT's primary goal is the development of novel active safety functions, to be finally demonstrated to the public in three prototype vehicles. A sound benefit assessment of the prototype vehicle's functionality requires a broad testing methodology which goes beyond what has currently been used. Since PROSPECT functions are developed to prevent accidents in intersections, a key aspect of the test methodology is the reproduction of natural driving styles on the test track with driving robots. For this task, data from a real driving study with subjects in a suburb of Munich, Germany was used. Further data from Barcelona will be available soon. The data suggests that intersection crossing can be broken down into five phases, two phases with straight deceleration / acceleration, one phase with constant radius and speed turning, and two phases where the bend is imitated or ended. In these latter phases, drivers mostly combine lateral and longitudinal accelerations and drive what is called a clothoid, a curve with curvature proportional to distance travelled, in order to change lateral acceleration smoothly rather than abrupt. The data suggests that the main parameter of the clothoid, the ratio distance travelled to curvature, is mostly constant during the intersections. This parameter together with decelerations and speeds allows the generation of synthetic robot program files for a reproduction of natural driving styles using robots, allowing a much greater reproducibility than what is possible with human test drivers. First tests show that in principle it is possible to use the driving robots for vehicle control in that manner; a challenge currently is the control performance of the robot system in terms of speed control, but it is anticipated that this problem will be solved soon. Further elements of the PROSPECT test methodology are a standard intersection marking to be implemented on the test track which allows the efficient testing of all PROSPECT test cases, standard mobile and light obstruction elements for quick reproduction of obstructions of view, and a concept for tests in realistic surroundings. First tests using the PROSPECT test methodology will be conducted over the summer 2017, and final tests of the prototype vehicles developed within PROSPECT will be conducted in early 2018
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.
Methods for analyzing the efficiency of primary safety measures based on real life accident data
(2009)
Primary safety measures are designed to help to avoid accidents or, if this is not possible, to stabilize respectively reduce the dynamics of the vehicle to such an extent that the secondary safety measures are able to act as good as possible. The efficiency of a primary safety measure is a criterion for the effectiveness, with which a system of primary safety succeeds in avoiding or mitigation the severity of accidents within its range of operation and in interactionwith driver and vehicle. Based on Daimler-´s philosophy of the "Real Life Safety" the reflection of the real world accidents in the systems range of operation is both starting point as well as benchmark for its optimization. This paper deals with the methodology to perform assessments of statistical representative efficiency of primary safety measures. To be able to carry out an investigation concerning the efficiency of a primary safety measure in a transparent and comparable way basic definitions and systematics were introduced. Based on these definitions different systematic methods for estimating efficiency were discussed and related to each other. The paper is completed by presenting an example for estimating the efficiency of actual "single" and "multi" connected primary safety systems.
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.
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.
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.
Accident research 2.0: New methods for representative evaluation of integral safety in traffic
(2013)
BMW has developed a procedure for rating Advanced Driver Assistance Systems (ADAS) benefits that integrates two distinct tools. The tool "S.A.F.E.R." is designed to analyze the pre-crash phase. The aim of S.A.F.E.R. is to simulate all relevant processes in sufficient detail to obtain reproducible estimates of key indicators (effectiveness, false positives, etc.). The relevant processes include not only traffic and vehicle dynamics, but also environmental and most importantly human factors. Representative distributions of factors and parameters are obtained by taking the stochastic variation of all relevant parameters into account in the simulations. The second tool, known as "ICOS", has been designed to provide a high-resolution, high-fidelity description of crash phase dynamics. If one converts the outputs of stochastic simulation into inputs for crash dynamics, the result is a comprehensive description of exactly how a safety system can reduce injuries. Applications currently focus on high-fidelity simulation of individual crashes in order to enhance our understanding and optimization of connected safety systems. An integrated simulation process thus allows an exact prediction of the effectiveness in individual cases in terms of injury severity. The development and rating of integral safety need to reflect the true efficiency in the field. The integrated approach described here could provide a valid and reproducible basis for rating connected systems of active and passive safety. In particular, "virtual experiments" using a traffic-based approach and incorporating models of all relevant processes constitute an essential element of the approach.
The advent of active safety systems calls for the development of appropriate testing methods. These methods aim to assess the effectivity of active safety systems based on criteria such as their capability to avoid accidents or lower impact speeds and thus mitigate the injury severity. For prospective effectivity studies, simulation becomes an important tool that needs valid models not only to simulate driving dynamics and safety systems, but also to resolve the collision mechanics. This paper presents an impact model which is based on solving momentum conservation equations and uses it in an effectivity study of a generic collision mitigation system in reconstructed real accidents at junctions. The model assumes an infinitely short crash duration and computes output parameters such as post-crash velocities, delta-v, force directions, etc. and is applicable for all impact collision configurations such as oblique, excentric collisions. Requiring only very little computational effort, the model is especially useful for effectivity studies where large numbers of simulations are necessary. Validation of the model is done by comparison with results from the widely used reconstruction software PC-Crash. Vehicles involved in the accidents are virtually equipped with a collision mitigation system for junctions using the software X-RATE, and the simulations (referred to as system simulations) are started sufficiently early before the collision occurred. In order to assess the effectivity, the real accident (referred to as baseline) is compared with the system simulations by computing the reduction of the impact speeds and delta-v.
There is a need for detecting characteristics of pedestrian movement before car-pedestrian collisions to trigger a fully reversible pedestrian protection system. For this purpose, a pedestrian sensor system has been developed. In order to evaluate the effectiveness of the sensor system, the in-depth knowledge of car-pedestrian impact scenarios is needed. This study aims at the evaluation of the sensor system. The accident data are selected from the STRADA database. The accident scenarios available in this database were evaluated and the knowledge of the most common scenarios was developed in terms of the pedestrian trajectory, the pedestrian speed, the car trajectory, the car velocity, etc. A mathematical model was then established to evaluate the sensor system with different detective angles. It was found that in order to detect all the pedestrians in the most common scenarios on time the sensor detective angle must be kept larger than 60 degrees.
The data situation for quantifying the proportion of accidents avoided by the introduction of active safety systems is incomplete, since there is generally no data available on the accidents avoided by the technology in question. In this paper, a split-register approach is suggested and compared with the classical case-control approach known from epidemiologic applications. Provided a set of assumptions hold, which can reasonably be made in such data situations, the split register approach allows inferences on the population accident risk. For both approaches the benefits of basing the analysis on the results of a logistic regression to adjust for confounding factors are outlined. The biasing effects of violating key assumptions are discussed and the split-register approach is demonstrated using the example of the active safety system ESP with data from the German in-depth accident study GIDAS.
The overall purpose of the ASSESS project is to develop a relevant and standardised set of test and assessment methods and associated tools for integrated vehicle safety systems, primarily focussing on currently available pre-crash sensing systems. The first stage of the project was to define casualty relevant accident scenarios so that the test scenarios will be developed based on accident scenarios which currently result in the greatest injury outcome, measured by a combination of casualty severity and casualty frequency. The first analysis stage was completed using data from a range of accident databases, including those which were nationally representative (STATS19, UK and STRADA, SE) and in-depth sources which provided more detailed parameters to characterise the accident scenarios (GIDAS, DE and OTS, UK). A common analysis method was developed in order to compare the data from these different sources, and while the data sets were not completely compatible, the majority of the data was aligned in such a way that allowed a useful comparison to be made. As the ASSESS project focuses on pre-crash sensing systems fitted to passenger cars, the data selected for the analysis was "injury accidents which involved at least one passenger car". The accident data analysis yielded the following ranked list of most relevant accident scenarios: Rank Accident scenario 1 Driving accident - single vehicle loss of control 2 Accidents in longitudinal traffic (same and opposite directions) 3 Accidents with turning vehicle(s) or crossing paths in junctions 4 Accidents involving pedestrians The ranked list highlights the relatively large role played by "accidents in longitudinal traffic", and "accidents with turning vehicle(s) or crossing paths in junctions" (the second and third most prevalent accident scenarios, respectively). The pre-crash systems addressed in ASSESS propose to yield beneficial safety outcomes with specific regard to these accident scenarios. This indicates that the ASSESS project is highly relevant to the current casualty crash problem. In the second stage of the analysis a selection of these accident scenarios were analysed further to define the accident parameters at a more detailed level .This paper describes the analysis approach and results from the first analysis stage.
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 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
Die EU hat für die Verkehrssicherheit in Europa ein anspruchsvolles Ziel vorgegeben: Bis 2010 soll die Anzahl der im Straßenverkehr Getöteten gegenüber 2000 halbiert werden. Für Deutschland kann eine erfolgreiche Zwischenbilanz gezogen werden: In den letzten 5 Jahren nahm trotz Vergrößerung des Kraftfahrzeugbestandes um 6% die Anzahl der Verkehrstoten um 29% ab, in den vergangenen 10 Jahren ist ein Rückgang um 43% zu verzeichnen. Diese im internationalen Vergleich überdurchschnittlichen Erfolge sind nicht zuletzt auch auf Fortschritte in der Fahrzeugtechnik zurückzuführen, wobei die zunehmende Verbreitung von Systemen der Aktiven Sicherheit wie ABS, BAS, ESP einen entscheidenden Anteil hat. Nach der deutlichen Reduzierung von Fahrunfällen durch ESP-® stehen nun die Auffahrunfälle im Fokus der Sicherheitsentwicklung von Mercedes-Benz. Das Paket aus verbessertem rückwärtigen Signalbild (Adaptives Bremslicht) und Brems-Assistent (BAS) wurde kürzlich durch radarbasierte Bremsassistenz ergänzt (BAS PLUS und PRE-SAFE-®-Bremse). Der Beitrag geht auf Funktion und Wirksamkeit der einzelnen Systeme ein und gibt einen Ausblick in die nähere Zukunft.
The utilisation of secondary-safety systems to protect occupants has attained a very high level over the past decades. Further improvements are still possible, but increasingly minor progress is only to be had with a high degree of effort. Thus, a key aspect must be the impact to overall safety in an accident. If reliable information is available on an imminent crash, measures already taken in the pre-crash phase can result in a significantly great influence on the outcomes of the crash. With this background preventive measures are the key to a sustainable further reduction of the figures of crash victims on our roads. This paper aims to show a preventive approach that can contribute to lessening the consequences of a crash by creating an optimum interaction of measures in the fields of primary and secondary safety. To further enhance vehicle safety, driver assistant systems are already available that warn the driver of an imminent front-to-rear-end crash. The next step is to support him in his reactions or if he fails to react sufficiently, to even initiate an automatic braking when the crash becomes unavoidable. Automatic pre-crash braking can, in an ideal situation, fully prevent a crash or can significantly reduce the impact speed and thus the impact energy (and the severity of the accident). If a vehicle is being braked in the pre-crash phase, the occupants are already being pre-stressed by the deceleration. The information available about the imminent crash can be used to activate the belt tensioners and likewise other secondary safety systems in the vehicle right before the impact. The pre-crash deceleration also causes the front of the vehicle to dip. Conventional crash tests do not take this specific impact situation into consideration. This is why, for example, the influences of the pre-crash displacements of the occupants are not recorded in the test results. Furthermore, a reproducible representation of the benefit of the vehicle safety systems which prepare the occupants for the imminent impact is not possible. In order to demonstrate the functions of automated pre-crash braking and to investigate the differences during the impact as a consequence of the altered occupant positions as well as the initiation of force and deformations of the vehicle front, DEKRA teamed up with BMW to carry out a joint crash test with the latest BMW 5 series vehicle. It involved the vehicle braking automatically from a starting test speed of 64 km/h (corresponding to the impact speed set by Euro NCAP) down to 40 km/h. The test was still run by the intelligent drive system of the crash test facility. This required several modifications to be made to the test facility as well as to the vehicle. The paper will describe and discuss some relevant results of the crash test. In addition, the possible benefits of such systems will also be considered. The test supplemented the work of the vFSS working group (vFSS stands advanced Forward-looking Safety Systems).