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Europe has benefited from a decreasing number of road traffic fatalities. However, the proportion of older road users increases steadily. In an ageing society, the SENIORS project aims to improve the safe mobility of older road users by determining appropriate requirements towards passive vehicle safety systems. Therefore, the characteristics of road traffic crashes involving the elderly people need to be understood. This paper focuses on car occupants and pedestrians or cyclists in crashes with modern passenger cars. Ten crash databases and four hospital statistics from Europe have been analysed to answer the questions on which body regions are most frequently and severely injured in the elderly, and specific injuries sustained by always comparing older (65 years and above) with midâ€aged road users (25â€64 years). It was found that the body region thorax is of particularly high importance for the older car occupant with injury severities of AIS2 or AIS3+, where as the lower extremities, head and the thorax need to be considered for older pedestrians and cyclists. Further, injury risk functions were provided. The hospital data analysis showed less difference between the age groups. The linkage between crash and hospital data could only be made on a general level as their inclusion criteria were quite different.
Advancing active safety towards the protection of vulnerable road users: the PROSPECT project
(2017)
Accidents involving Vulnerable Road Users (VRU) are still a very significant issue for road safety. According to the World Health Organisation, pedestrian and cyclist deaths account for more than 25% of all road traffic deaths worldwide. Autonomous Emergency Braking Systems have the potential to improve safety for these VRU groups. The PROSPECT project (Proactive Safety for Pedestrians and Cyclists) aims to significantly improve the effectiveness of active VRU safety systems compared to those currently on the market by expanding the scope of scenarios addressed by the systems and improving the overall system performance. The project pursues an integrated approach: Newest available accident data combined with naturalistic observations and HMI guidelines represent key inputs for the system specifications, which form the basis for the system development. For system development, two main aspects are considered: advanced sensor processing with situation analysis, and intervention strategies including braking and steering. All these concepts are implemented in several vehicle prototypes. Special emphasis is put on balancing system performance in critical scenarios and avoiding undesired system activations. For system validation, testing in realistic scenarios will be done. Results will allow the performance assessment of the developed concepts and a cost-benefit analysis. The findings within the PROSPECT project will contribute to the generation of state -of-the-art knowledge, technical innovations, assessment methodologies and tools for advancing Advanced Driver Assistance Systems towards the protection of VRUs. The introduction of a new generation safety system in the market will enhance VRU road safety in 2020-2025, contributing to the "Vision Zero" objective of no fatalities or serious injuries in road traffic set out in the Transport White Paper. Furthermore, the test methodologies and tools developed within the project shall be considered for the New Car Assessment Programme (Euro NCAP) future roadmaps, supporting the European Commission goal of halving the road toll in the 2011-2020 timeframe.
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.
Die Bundesanstalt für Straßenwesen (BASt) bringt zum Ende jeden Jahres eine Prognose der Unfall- und Verunglücktenzahlen des noch laufenden Jahres heraus, um so über die Entwicklung der Verkehrssicherheit in Deutschland Bilanz ziehen zu können. Dabei wird das Unfallgeschehen nach dem Schweregrad der Konsequenzen, der Ortslage sowie Alter und Art der Verkehrsbeteiligung der Verunglückten in 27 Zeitreihen unterteilt. Zu diesem Zeitpunkt sind die Daten lediglich für die ersten acht oder neun Monate erhältlich. Um Bilanz zu ziehen, werden die Anzahlen der letzten drei oder vier Monate prognostiziert. Gesamtziel des hier beschriebenen Forschungsvorhabens ist die Optimierung der jährlichen Unfallprognosen durch Anwendung von strukturellen Zeitreihenmodellen, bei denen die Vorhersagen aus dem Trend der vorliegenden Monate, und der Dynamik der vorhergehenden Jahre abgeleitet werden. Um dem Einfluss der Witterungsverhältnisse Rechnung zu tragen, werden dabei meteorologische Variablen in das Vorhersagemodell aufgenommen. Um die Modelle zu testen, werden die endgültigen Daten der letzten 15 Jahre jeweils aus den vorläufigen Daten der ersten Monate vorhergesagt und mit den tatsächlich beobachteten endgültigen Unfall- und Verunglücktenzahlen verglichen. Die Resultate zeigen, dass im Vergleich zu den bisherigen Vorhersagen mithilfe der hier vorgestellten Modelle die Vorhersagen für 25 der 27 Reihen präziser werden. Lediglich zwei Reihen zeigen einen leichten Anstieg des Vorhersagefehlers. Beim Vergleich von Modellen mit und ohne meteorologischen Variablen zeigt sich, dass 23 der 27 Reihen besser vorhergesagt werden können, wenn man das Wetter berücksichtigt. Neben der verbesserten Vorhersage ermöglicht die Aufnahme der Wettervariablen auch eine Einschätzung, wie groß der Einfluss der Witterungsgegebenheiten auf das Unfallgeschehen ist. Es zeigt sich also, dass die Anwendung von strukturellen Zeitreihenmodellen und die Berücksichtigung von meteorologischen Variablen zu einer deutlichen Verbesserung der Vorhersagegenauigkeit führen. Die Verbesserung der Vorhersagen durch die Aufnahme von Wettervariablen bestätigt nochmals den Einfluss der Witterungsumstände auf das Unfallgeschehen.
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.
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.
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.
Powered Two Wheeler (Motorcycle) crashes are overrepresented in EU, England, and United States casualty statistics for both fatal and serious injuries. While regional geographic differences are evident for motorcycle size, type, and engine displacement, the casualty statistics consistently indicate significantly higher injury rates for all motorcycle riders when compared to car occupants. Accident analysis and reconstruction of these motorcycle crashes is a necessary process to gain further understanding of potential injury mitigation strategies. This paper focuses on the analysis of the rider post impact trajectory in the immediate moments following a crash. The rider and motorcycle, while loosely coupled by seating position leading up to a crash, quickly decouple as the crash forces develop. As a result, the rider moves relative to the motorcycle and relative to the collision partner. This movement, or trajectory, is primarily influenced by the type and configuration of the impact, the type and configuration of the motorcycle and collision partner, and the speeds involved. Understanding the rider's post impact trajectory will assist in the development of injury mitigation strategies. Both the free flight trajectory of the rider and the rider's trajectory as influenced by interaction with the motorcycle and collision partner are examined. Rider trajectories in full scale crash testing and real world motorcycle crashes are both studied and presented. The resulting physical evidence that can be observed by an accident analyst is discussed. The application of projectile motion physics is analyzed and the necessary input parameters, such as initial launch angle, are studied. This study will assist in understanding the post-impact dynamics of a motorcyclist, and will provide useful information to analysts evaluating real world crashes.
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.