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The incidence of side impacts was investigated from GIDAS data. Both vehicle-fixed object and vehicle-vehicle collisions were analysed as these are enclosed within the consumer testing program. Vehicle-fixed object collisions were stratified according to ESC availability. Results indicated that vehicles equipped with ESC rarely have pure-lateral impacts. An increase in oblique collisions was seen for the vehicles with ESC whereby most vehicle were driving in left curves. The analysis of vehicle-vehicle collisions developed injury risk curves were developed at the AIS3+ injury severity for the vehicle-vehicle side impacts. Results suggested that greatest injury risk occurred when a Pre Euro NCAP vehicle was struck by a Post Euro-NCAP vehicle. The remaining curves did not show different behaviour, indicating that stiffness increased have been equally combated. This was attributable to the few Post Euro-NCAP vehicles that had a deployed curtain airbag available in the sample. The integration of Euro NCAP testing has shown to improve vehicle crashworthiness for pole collisions, as those vehicles with ESC rarely incur lateral impacts.
The Decision Support System (DSS) is one of the key objectives of the European co-funded research project SafetyCube in order to better support evidence-based policy making. Results will be assembled in the form of a DSS that will present for each suggested road safety measure: details of risk factor tackled, measure, best estimate of casualty reduction effectiveness, cost-benefit evaluation and analytic background. The development of the DSS presents a great potential to further support decision making at local, regional, national and international level, aiming to fill in the current gap of comparable measures effectiveness evaluation. In order to provide policy-makers and industry with comprehensive and well-structured information about measures, it is essential that a systems approach is used to ensure the links between risk factors and all relevant safety measures are made fully visible. The DSS is intended to become a major source of information for industry, policy-makers and the wider road safety community.
Driver distraction
(2017)
This report for the Institute of Advanced Motorists (IAM) summarises recent research and knowledge from scientific studies about distracted driving. The report defines what it means to be "distracted" when driving, discusses the impact of distraction on driver behaviour and safety, and what can be done to reduce distracted driving. The focus of distraction discussed here relates to how drivers engage with technology when driving. The report begins with a background to driver distraction, followed by discussion about what is actually meant by driver distraction. It is then considered why humans cannot successfully do two things at the same time, particularly within the context of driving. The subsequent section summarises the scientific research findings to date with regard to driver distraction and technology, and how this affects different types of road user. Recommendations for how driver distraction can be mitigated in the real world and a summary conclude the report. Responses to common questions raised by drivers are presented in Appendix A.
Twenty-eight percent of traffic accidents in Japan are rear-end collisions, and of these, 13% are multiple collisions (three or more vehicles and/or roadside objects). A post-crash braking system enables the driver to stop the vehicle in a short distance after a rear-end collision to prevent secondary collisions. In this study, the effectiveness of a post-crash braking system was examined using a drive recorder database. In 64% of rear-end collisions, the driver's braking was interrupted after the collision. The stopping distance was estimated with time data from the drive recorder. We predict that the brake assist would be effective in preventing secondary collisions in 21% of cases.
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.
[Introduction:] A large number of road users involved in road traffic crashes recover from their injuries, but some of them never recover fully and suffer from some kind of permanent disability. In addition to loss of life or reduced quality of life, road accidents carry many and diverse consequences to the survivors such as legal implications, economic burden, job absences, need of care from a third person, home and vehicle adaptations as well as psychological consequences. Within an EU funded project MOVE/C4/SUB/2011-294/SI2.628846 (REHABIL AID) these consequences were analyzed more detailed.
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.
Bus or heavy vehicle passenger accidents are rare events, compared with car accidents, but sometimes leads to a large number of victims especially in rollover crash scenarios. Two accidents occurred in Portugal in 2007 and 2013 in which 28 people died and more than 50 are injured, shown the importance of the investigation of such accidents. For the investigation of these accidents multidisciplinary teams are constituted with engineers and police officers. All the factors involved are taken into consideration including road design, traffic signs, maintenance and hardware, human factors, and vehicle factors. In this work a methodology to an accurate collection of the data is proposed. From the information collected the accident is reconstructed using the PC-CrashTM software. From this all the contribution factors are determined and recommendations to mitigate these crashes are listed. These two accidents are rollover accidents and the analysis of the injuries and its correlation with the use of retention systems is very important. From the medical data and with the dynamics of the accident determined simulations of the occupants with biomechanical models are carried out in order to evaluate the effect of the retention systems in the injuries. This analysis is based on injury criteria (such as Abbreviated Injury Score (AIS) or Injury Severity Scale (ISS)). With this it is possible to determine if the seat belt was worn or not.
Recently, EuroNCAP updated the upper legform test protocols. The main objective of this study is to establish the upper legform test in KIDAS (Korean In-depth Accident Study) taking into account domestic pedestrian accident data as well as anthropometric data to protect elderly pedestrians whose average height and weight is much smaller and lighter than other age groups, especially compared to Europeans. Therefore 230 cases of pedestrian accidents from KIDAS were investigated to explore the injury severity of body regions as well as age related injury patterns. Injuries of all body regions were examined, with a special focus on injuries of abdomen and pelvic area. On the other hand, in order to explore Korea's pedestrian accident environment, national police data and KIDAS (Korean In-depth Accident Study) data were compared. The results should be taken into account in future analyses and possible improvements, such as regulations and KNCAP test protocols, of the pedestrian safety policy in Korea.
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.