Sonstige
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.
Cyclists are more likely to be injured in fatal crashes than motorised vehicles. To gain detailed and precise behavioural data of road users, i.e. trajectories, a measuring campaign was conducted. Therefore, a black-spot for accidents with cyclists in Berlin, Germany was selected. The traffic has been detected by a fully automated traffic video analysis system continuously for twelve hours. The video surveillance system is capable of automatically extracting trajectories, classifying road user types and precise determining and positioning of conflicts and accidents. Additionally, pre-conflict and pre-accident situations could be analysed to provide further in-depth understanding of accident causation. The evaluation of the measuring campaign comprised the investigation of traffic parameters, e.g. traffic flow, as well as traffic-safety related parameters based on Surrogate Safety Measures (SSM). Furthermore, the spatial and temporal distributions of conflicts involving cyclists were determined. As a result, three possible conflict clusters could be identified, of which one cluster could be confirmed by detailed video analysis, showing conflicts caused by right turning vehicles.
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.
The NHTSA-sponsored Crash Injury Research and Engineering Network (CIREN) has collected and analyzed crash, vehicle damage, and detailed injury data from over 4000 case occupants who were patients admitted to Level-I trauma centers following involvement in motor vehicle crashes. Since 2005, CIREN has used a methodology known as "BioTab" to analyze and document the causes of injuries resulting from passenger vehicle crashes. BioTab was developed to provide a complete evidenced-based method to describe and document injury causation from in-depth crash investigations with confidence levels assigned to the causes of injury based on the available evidence. This paper describes how the BioTab method is being used in CIREN to leverage the data collected from in-depth crash investigations, and particularly the detailed injury data available in CIREN, to develop evidence-based assessments of injury causation. CIREN case examples are provided to demonstrate the ability of the BioTab method to improve real-world crash/injury data assessment.
In Germany, in-depth accident investigations are carried out in the Hannover area since 1973. In 1999 a second region was added with surveys in Dresden and the surrounding area. Internationally, the acronym GIDAS (German In-Depth Accident Study) is commonly used for these surveys. Compared to many other countries, the sample sizes of the GIDAS surveys are much larger. The goal is to collect 1.000 accidents involving personal injuries per year and region. Data collection takes place by using a sampling procedure, which can be interpreted as a two-stage process with time intervals as primary units and accidents as secondary units. An important question is, to what extend these samples are representative for the target population from which they are drawn. Analyses show, for example, that accidents with persons killed or seriously injured are overrepresented in the samples compared to accidents with slightly injured persons. This means, that these data are subject to biases due to uncontrolled variation of sample inclusion probability. Therefore, appropriate weighting and expansion methods have to be applied in order to adjust or correct for these biases. The contribution describes the statistical and methodological principles underlying the GIDAS surveys with respect to sampling procedure, data collection and expansion. In addition, some suggestions regarding potential improvements of study design are made from a methodological point of view.
Road accidents are typically analyzed to address influences of human, vehicle, and environmental (primarily infrastructure) factors. A new methodology, based on a "Venn diagram" analysis, gives a broader perspective on the probable factors, and combinations of factors, contributing both to the occurrence of a crash and to sustaining injuries in that crash. The methodology was applied to 214 accidents on the Mumbai-Pune expressway. Factors contributing to accidents and injuries were addressed. The major human factors influencing accidents on this roadway were speeding (30%) and falling asleep (29%), while injuries were primarily due to lack of seat belt use (46%). The leading infrastructure factor for injuries was impact with a roadside manmade structure (28%), and the main vehicle factor for injuries was passenger compartment intrusion (73%). This methodology can help identify effective vehicle and infrastructure-related solutions for preventing accidents and mitigating injuries in India.
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.
In the last years various new driver information and driver assistance systems made their way into modern vehicles and there are yet countless systems underway. However, expenses for both, the development and the construction of these systems are tremendous. Therefore the interest of evaluating systems keeps growing steadily, not only regarding the results of systems developed in the last years but also regarding system ideas. Only if at least a rough benefit estimation is given, the industry can decide which development should be supported. However, there is still a lack of transparency of possible and useful methods for these kinds of estimations. These were analyses and structured in this study.
Whiplash injuries are characterized by the high variability of its symptoms and by the subjectivity of its diagnosis, which sometimes leads to frauds perpetrated by victims of rear-end impacts. It is estimated that whiplash injuries cost annually about 10.000 million Euros in Europe. Therefore, the aim of this study was to investigate the influence of the dynamics of the accident in which the victim was involved in the probability of development of whiplash associated injuries. In the presented methodology, first an accident reconstruction is performed where the dynamics of the accident is determined. This is carried out using the software PC-Crash, police and insurance companies' data. Then biomechanical injuries criteria related with whiplash injuries are evaluated. For the evaluation of the probability of having whiplash injuries, the Neck Injury Criterion (NIC) of the victim and the mean acceleration of the vehicle were evaluated. Then, with medical reports, the results of the accident reconstruction are correlated with the reported injuries. Some examples are presented. The results obtained indicate that the study of the dynamics of the road accidents in which the victims were involved could be used as an auxiliary of the prognosis of whiplash injuries and is important for a precise diagnosis of this type of injuries.