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Institut
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 this study, the mean profile depth (MPD) that expresses roughness of road pavements was calculated using the road survey equipment vehicle and the calculated MPD was compared with the real number of traffic accidents. The analysis method used in this study was to classify the appropriate clustering in relation to traffic accidents using the K-means clustering and to compare this with the presence of traffic accidents via the MPDs to derive the result. K-means clustering was used in the analysis method and four clusters were found using the clustering analysis results. The center of each cluster was 0.627, 0.850, 1.118, and 1.237, respectively. The result of this study is expected to be utilized as foundational research in the traffic safety area.
Still correlated with high mortality rates in traffic accidents traumatic aortic ruptures were frequently detected in unprotected car occupants in the early years. This biomechanical analysis investigates the different kinds of injury mechanisms leading to traumatic aortic injuries in todays traffic accidents and how the way of traffic participation affects the frequency of those injuries over the years. Based on GIDAS reported traffic accidents from 1973 to 2014 are analyzed. Results show that traumatic aortic injuries are mainly observed in high-speed accidents with high body deceleration and direct load force to the chest. Mostly chest compression is responsible for the load direction to the cardiac vessels. The main observed load vector is from caudal-ventral and from ventral solely, but also force impact from left and right side and in roll-over events with chest compression lead to traumatic aortic injuries. Classically, the injury appeares at the junction between the well-fixed aortic arch and the pars decendens following a kind of a scoop mechanism, a few cases with a hyperflexion mechanism are also described. In our analysis the deceleration effect alone never led to an aortic rupture. Comparing the past 40 years aortic injuries shift from unprotected car occupants to today's unprotected vulnerable road users like pedestrians, cyclists and motorcyclists. Still the accident characteristics are linked with chest compression force under high speed impact, no seatbelt and direct body impact.
The presence and performance of Advanced Driver Assistance Systems (ADAS) has increased over last years. Systems available on the market address also conflicts with vulnerable road users (VRUs) such as pedestrians and cyclists. Within the European project PROSPECT (Horizon2020, funded by the EC) improved VRU ADAS systems are developed and tested. However, before determining systems" properties and starting testing, an up-to-date analysis of VRU crashes was needed in order to derive the most important Use Cases (detailed crash descriptions) the systems should address. Besides the identified Accident Scenarios (basic crash descriptions), this paper describes in short the method of deriving the Use Cases for car-to-cyclist crashes. Method Crashes involving one passenger car and one cyclist were investigated in several European crash databases looking for all injury severity levels (slight, severe and fatal). These data sources included European statistics from CARE, data on national level from Germany, Sweden and Hungary as well as detailed accident information from these three countries using GIDAS, the Volvo Cars Cyclist Accident database and Hungarian in-depth accident data, respectively. The most frequent accident scenarios were studied and Use Cases were derived considering the key aspects of these crash situations (e.g., view orientation of the cyclist and the car driver- manoeuvre intention) and thus, form an appropriate basis for the development of Test Scenarios. Results Latest information on car-to-cyclist crashes in Europe was compiled including details on the related crash configurations, driving directions, outcome in terms of injury severity, accident location, other environmental aspects and driver responsibilities. The majority of car-to-cyclist crashes occurred during daylight and in clear weather conditions. Car-to-cyclist crashes in which the vehicle was traveling straight and the cyclist is moving in line with the traffic were found to result in the greatest number of fatalities. Considering also slightly and seriously injured cyclists led to a different order of crash patterns according to the three considered European countries. Finally the paper introduced the Use Cases derived from the crash data analysis. A total of 29 Use Cases were derived considering the group of seriously or fatally injured cyclists and 35 Use Cases were derived considering the group of slightly, seriously or fatally injured cyclists. The highest ranked Use Case describes the collision between a car turning to the nearside and a cyclist riding on a bicycle lane against the usual driving direction. A unified European dataset on car-to-cyclist crash scenarios is not available as the data available in CARE is limited, hence national datasets had to be used for the study and further work will be required to extrapolate the results to a European level. Due to the large number of Use Cases, the paper shows only highest ranked ones.
Causation of traffic accidents with children from the perspective of all involved participants
(2017)
In the year 2014 about 2,800 children between zero and 14 years got injured due to traffic accidents in Austria. More than 50% were taking part in traffic as active road users like cyclists or pedestrians. Within this study 46 real world traffic accidents between vehicles and children as pedestrians were analysed. In 39 cases, car drivers hit the crossing children. In the other cases, the collision opponents were busses, trucks or motorcycles. Most of the children got hit while crossing a road at urban sites. By analysing the traffic accidents from the perspectives of all involved participants, vehicle drivers and injured children, it is possible to identify factors for each participant, which led to the accident and factors that contributed the accident. The main task is to find patterns in the behaviour of crash victims (children and driver) before the collision. One important fact is that in more than 50% of the analysed cases sight obstructions were an important contributing factor for both, the driver and the child. From drivers view situations in which the child moved unexpected into the driven road lane were often found. For the injured child, factors like: no attention to the road traffic or no sufficient traffic observation were found to be relevant. Further it- possible to sensitise children and adults to possible source of critical traffic situations according to the findings of this study.
In this study, we compared the injury severity of occupants according to the seating position and the crashing direction in motor vehicle accidents. In the driver's point of view, it was separated the seating position as "Near-side" and "Far-side". The study subjects were targeted by people who visited 4 regional emergency centers following motor vehicle accidents. Real-world investigation was performed by direct and indirect methods after patient- consent. The information of the damaged vehicle was informed by Collision Deformation Classification (CDC) code and the information of the injury of patients was informed by using the Abbreviated Injury Score (AIS) and Injury Severity Score (ISS). When the column 3 in CDC code was P, damaged at the middle part of lateral side, the average point of AIS 3 was 1.91-±1.72 in near-side and 1.02-±1.31 in far-side (p<0.01). The average point of maximum AIS (MAIS) was 2.78-±1.39 in near-side and 2.02-±1.11 in far-side (p<0.01). The average point of ISS was 15.74-±14.71 in near-side and 8.11-±8.39 in far-side (p<0.01). Also, when the column 3 in CDC code was D, damaged at the whole part of lateral side, it was significant that the average point of AIS 3 and MAIS in near-side was bigger than in far-side (p=0.02).
For the determination of the road surface roughness common methods have been established, like Skid Resistance Tester (SRT) or the Sideway-force Coefficient Routine Investigation Machine (SCRIM). Both methods are used to measure a comparable and reliable maximum friction potential value and to assess the quality of the road surface. However, the comparison of the measurements under real conditions and the results of measurements with SRT and SCRIM showed only minor correlations. The paper shows the comparison between these standardised methods and real vehicle braking tests and discusses the results.
The levels of continuous vehicle automation have become common knowledge. They facilitate overall understanding of the issue. Yet, continuous vehicle automation described therein does not cover "automated driving" as a whole: Functions intervening temporarily in accident-prone situations can obviously not be classified by means of continuous levels. Continuous automation describes the shift in workload from purely human driven vehicles to full automation. Duties of the driver are assigned to the machine as automation levels rise. Emergency braking, e.g., is obviously discontinuous and intensive automation. It cannot be classified under this regime. The resulting absence of visibility of these important functions cannot satisfy " especially in the light of effect they take on traffic safety. Therefore, in order to reach a full picture of vehicle automation, a comprehensive approach is proposed that can map out different characteristics as "Principle of Operation" at top level. On this basis informing and warning functions as well as functions intervening only temporarily in near-accident situations can be described. To reach a complete picture, levels for the discontinuous, temporarily intervening functions are proposed " meant to be the counterpart of the continuous levels already in place. This results in a detailed and independent classification for accident-prone situations. This finally provides for the visibility these important functions deserve.
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.
At IAM RoadSmart we share the excitement about autonomous cars " who wouldn't! However over half of the drivers we polled supported concentrating on making drivers safer " among IAM RoadSmart members it was 70%. Driverless cars are still years away but delivering safer drivers can help reduce death and injury from tomorrow. Governments, academics and car makers need to work hard to convince sceptical British and American drivers that autonomous cars can deliver the benefits promised such as a 90% plus reduction in road deaths.
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.
Road condition acquisition and assessment are the key to guarantee their permanent availability. In order to maintain a country's whole road network, millions of high-resolution images have to be analyzed annually. Currently, this requires cost and time excessive manual labor. We aim to automate this process to a high degree by applying deep neural networks. Such networks need a lot of data to be trained successfully, which are not publicly available at the moment. In this paper, we present the GAPs dataset, which is the first freely available pavement distress dataset of a size, large enough to train high-performing deep neural networks. It provides high quality images, recorded by a standardized process fulfilling German federal regulations, and detailed distress annotations. For the first time, this enables a fair comparison of research in this field. Furthermore, we present a first evaluation of the state of the art in pavement distress detection and an analysis of the effectiveness of state of the art regularization techniques on this dataset.
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.
This paper gives an overview of the in-depth crash investigation activity conducted by the Centre for Automotive Safety Research (CASR) at the University of Adelaide, in South Australia. Recent changes in method include: an expansion in on-call hours for the crash investigation team, providing the option of a phone interview for crash participants to discuss the crash, and downloading objective crash data from vehicle airbag control modules. These changes have resulted in: increased representativeness of crashes by hour of day; a decrease in the over-representation of fatal crashes in our sample; an increase in the proportion of crashes that involved a pedestrian, bicycle or scooter (moped); an increase in the proportion of crash participants consenting to an interview; and an increase in the objective data available, through airbag control module downloads. Our in-depth crash investigations enabled research into road departures that found barriers were a more feasible solution than clear zones for eliminating serious and fatal injury resulting from run off road crashes.
Although road infrastructure is developed extensively Brazil is still one of the countries with the most dangerous roads in the world. In order to stop the increasing trend of traffic fatalities of the last few years and to improve traffic safety on Brazilian roads a pilot study on behalf of SAE Brazil started in March 2016 with the goal to lay the foundations for a long-term research activity. Piloting for an in-depth accident investigation the city of Campinas, roughly 100 km north of São Paulo was chosen. The pilot project was carried out with the local partner, the Empresa Municipal de Desenvolvimento de Campinas (EMDEC). The paper reports on the initial training of evidence based accident data collection on-spot, the implementation of the new digital database, the data collection and the first results. An outlook on the planned long-term accident investigations is given.
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.