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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.
Injury probability functions for pedestrians and bicyclists based on real-world accident data
(2017)
The paper is focusing on the modelling of injury severity probabilities, often called as Injury Risk Functions (IRF). These are mathematical functions describing the probability for a defined population and for possible explanatory factors (variables) to sustain a certain injury severity. Injury risk functions are becoming more and more important as basis for the assessment of automotive safety systems. They contribute to the understanding of injury mechanisms, (prospective) evaluation of safety systems and definition of protection criteria or are used within regulation and/or consumer ratings. In all cases, knowledge about the correlation between mechanical behavior and injury severity is needed. IRFs are often based on biomechanical data. This paper is focusing on the derivation of injury probability models from real world accident data of the GIDAS database (German In-depth Accident Study). In contrast to most academic terms there is no explicit term definition or definition of creation processes existing for injury probability models based on empirical data. Different approaches are existing for such kind of models in the field of accident research. There is a need for harmonization in terms of the used methods and data as well as the handling with the existing challenges. These are preparation of the dataset, model assumptions, censored/unknown data, evaluation of model accuracy, definition of dependent and independent variable, and others. In the presented study, several empirical, statistical and phenomenological approaches were analyzed regarding their advantages and disadvantages and also their applicability. Furthermore, the identification of appropriate prediction parameters for the injury severity of pedestrians has been considered. Due to its main effect on injuries of pedestrians and bicyclists, the importance of the secondary impact has also been analyzed. Finally, the model accuracy, evaluated by several criteria, is the rating factor that gives the quality and reliability for application of the resulting models. After the investigation and evaluation of statistical approaches one method was chosen and appropriate prediction variables were examined. Finally, all findings were summarized and injury risk functions for pedestrians in real world accidents were created. Additionally, the paper gives instructions for the interpretation and usage of such functions. The presented results include IRFs for several injury severity levels and age groups. The presented models are based on a high amount of real world accidents and describe very well the injury severity probability of pedestrians and bicyclists in frontal collisions with current vehicles. The functions can serve as basis for the evaluation of effectiveness of systems like Pedestrian-AEB or Bicycle-AEB.
Interaction of road environment, vehicle and human factors in the causation of pedestrian accidents
(2005)
The UK On-the-Spot project (OTS) completed over 1500 in-depth investigations of road accidents during 2000-2003 and is continuing for a further 3 years. Cases were sampled from two regions of England using rotating shifts to cover all days of the week and all hours of the day and night. Research teams were dispatched to accidents notified to police during the shifts; arrival time to the scene of the accident was generally less than 20 minutes. The methodology of OTS includes sophisticated systems for describing accident causation and the interaction of road, vehicle and human factors. The purpose of this paper is to describe and illustrate these systems by reference to pedestrian accidents. This type of analysis is intended to provide an insight into how and why pedestrian accidents occur in order to assist the development of effective road, vehicle and behavioural countermeasures.
Die Lastübertragung von den Fahrzeugrädern auf die Fahrbahntafel wird beschrieben, und es wird eine Übersicht der ermüdungsempfindlichen Schweissnahtbereiche von Deckblech, Längssteifen und Querträgern gegeben. Die charakteristischen Schwachpunkte der Schweissverbindungen werden in Skizzen dargestellt.
The European Union has set a target to reduce all road fatalities (over 40,000) with 50% in 2010. This target percentage remained unchanged with the introduction of the ten new member states within the EU as by May 1st, 2004. According to Eurostat, 34% of all fatalities in 1998 in the, then, fifteen states of the European Union were the result of single vehicle collisions. This represents over 14,000 lives lost each year of which many can likely be saved through better roadside infrastructure design. The challenge for road safety professionals is to find methods and design strategies that help to reduce these casualties. Procedures for full-scale vehicle crash testing of guard rails were first published in the US in 1962. Present European regulation is mainly based on these procedures and later developments. Since then the vehicle fleet has changed considerably. Due to the complexity of the actual safety problem the numerical simulation approach offers a good opportunity to evaluate the different parameters involved in road safety, such as infrastructure properties, vehicle type, vehicle occupants and injuries. The ideal situation would be that simulation tools are coupled or integrated and all involved effects would be related. At the moment this is not the case yet, but initiatives are taken and a new virtual era has started. This paper offers a method looking at two components that encompass the driving environment: the car and the guardrail. As part of the EC-funded project, RISER (Roadside Infrastructure for Safer European Roads) a multi body simulation program study is carried out to determine sensitivities of some parameters in car to guardrail collisions and gives insides in performance of the car with passive safety equipment, the guardrail and the interaction of these objects with each other. By offering a set of methods that includes these two aspects and their intertwining relations, more confidence can be gained in actually reducing fatalities due to single vehicle collisions with, or due to, roadside furniture. Reducing the number of fatalities of single vehicle crashes would contribute greatly to the stated goal of reducing casualties altogether.
Since 2008, the authors inspected fatal traffic accidents on the spot every year, with the cooperation of Toyota police station in Aichi pref. In the jurisdiction, numbers of fatal accidents were 18 in 2008, 12 in 2009, 14 accidents in 2010, and 16 in 2011. We here report the results of our analysis of information obtained by detailed inspection for those that occurred from 2008 to 2010. We focused on vehicle-to-pedestrian accidents, which accounted for about 45% of all accidents in 2008. Because many accidents occurred on residential roads not far from pedestrians" homes, it was revealed that the decrease of the collision speed by traffic calming such as humps and zone speed management, was highly effective. On the other hand, pedestrian detection technologies seemed to be also effective as a countermeasure on vehicle side. Every pedestrian position against a vehicle was clarified and TTC (Time to Collision) was calculated provisionally. Pedestrian accidents in intersections were also examined. Among the intersection pedestrian accidents within the jurisdiction, compared with the national average in Japan, the ratio of intersections without a signal and the ratio without a pedestrian crossing were high. According to the comparison of the Japanese traffic accident patterns between 2001 and 2008, pedestrian accidents during turning right and turning left did not decrease much. For elderly drivers, these accidents occurred very often. Finally, single vehicle accidents were analysed with the accident pattern analysis methods used above. There were high numbers of single vehicle accidents against object on single roads. Although fatal accidents against guardrails decreased, the numbers of fatal accidents against a utility pole and a sign pole were nearly constant. As for the impact with narrow width objects such as utility poles, the fatality rate was very high, and countermeasures of both road infrastructure and vehicles seem to be effective.
The proportion of older road users is increasing because of demographic change (in the group 65+ from current 18% to about 24% by 2030). The mobility needs of people 65+ often differ from those of younger people. Seniors (65+) are already more involved in fatal accidents than younger road users. According to the age development, the senior share of road deaths in the EU of today is increasing nearly one-fifth to one-third. From the in-depth analysis of accidents generic simulation models were developed. Attention has been paid both to psycho-physical characteristics as well as on the social and physical environment and their specifics in conjunction with seniors. By simulating the defined scenarios and varying the defined relevant parameters, accident influencing factors were examined as a basis for avoidance. In addition, the parameters were varied to show the influence from the vehicle, the pedestrian and the infrastructure to avoid the accident or to characterize the conditions for which the accident is inevitable.
In a first step, we have examined approximately 23 000 single vehicle accidents within the Austrian National Statistics database. In a second step, we considered 15% of all fatal "running off the road" accidents that occurred in Austria in 2003. As a result, two accident categories were specified; "leaving the road without preceding manoeuvre" and "leaving the road with preceding manoeuvre". These two categories can be basically characterised by the vehicle- heading angle and its velocity angle. In this report, we further suggest theoretical approaches for the dimensioning of a safety zone, an area adjacent to the road free of fixed objects or dangerous slopes. We also show the link between the two accident categories mentioned above and the real world accidents analysed in detail. These observations also form the basis for the required length for safety devices. Finally, we summarise accident avoidance strategies.
Data concerning accidents involving personal injury which have been collected in the context of in-depth investigations on scene in the Hannover area since 1973 and in the Dresden area since 1999 represent an important basis for empirical traffic safety research. At national and international level various analyses and comparisons are carried out on the basis of "in-depth data" from the above mentioned investigations. In-depth data play a decisive role e.g. within the validation of EuroNCAP results on secondary safety (crashworthiness) of individual passenger car models. Thus, statistically sound methods of data analysis and population parameter estimation are of high importance. Since the 1st of August 1984 the "in-depth investigations on scene" in the Hannover area have been carried out according to a sampling plan developed by HAUTZINGER in the context of a research project on behalf of BASt. In the meantime a second region of in-depth investigation on scene was added with surveys in Dresden and the surrounding area. Internationally, the acronym GIDAS (German In-Depth Accident Study) is commonly used for the two above mentioned surveys. The objective of a current research project (topic of this contribution) is, among other things, to examine and adjust the previous weighting and expansion method for the two regional accident investigations to the current general conditions.
Empirical vehicle crashworthiness studies are usually based on national or in-depth traffic accident surveys: Data on accident-involved cars/drivers are analysed in order to quantify the chance of driver injury and to assess certain risk factors like car make and model. As the cars/drivers involved in the same accident form a "cluster", where the size of the cluster equals the number of accident-involved parties, traffic accident survey data are typical multi-level data with accidents as first-level or primary and cars/drivers as secondlevel or secondary units (car occupants in general are to be considered as third level units). Consequently, appropriate statistical multi-level models are to be used for driver injury risk estimation purposes as these models properly account for the cluster structure of traffic accident survey data. In recent years various types of regression models for clustered data have been developed in the statistical sciences. This paper presents multi-level statistical models, which are generally applicable for vehicle crashworthiness assessment in the sense that data on single and multiple car crashes can be analysed simultaneously. As a special case of multi-level modelling driver injury risk estimation based on paired-by-collision car/driver data is considered. It is demonstrated that assessment results may be seriously biased, if the cluster structure inherent in traffic accident survey data is erroneously ignored in the data analysis stage.