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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.
Analysis of pedestrian leg contacts and distribution of contact points across the vehicle front
(2015)
Determining the risk to pedestrians that are impacted by areas of the front bumper not currently regulated in type-approval testing requires an understanding of the target population and the injury risk posed by the edges of the bumper. National statistics show that approximately 10% of all accident casualties are pedestrians, with 20% to 30% of these pedestrian casualties being killed or seriously injured. However, the contact position across the front of the bumper is not recorded in national statistics and so in-depth accident databases (OTS, UK and GIDAS, Germany) were used to examine injury risk in greater detail. The results showed that some injury types and severities of injuries appear to peak around the bumper edges. Although there are sometimes inconsistencies in the data, generally there is no evidence to suggest that the edges of the bumper are less likely to be contacted or cause injury.
The National Highways Development Project in India is aimed at upgrading over 12,000 km of national highways from 2-lane undivided roads to 4-lane divided roads. With nearly 40% of fatal crashes being reported on national highways, the effect of this project on road safety needs to be assessed. Researchers carried out on-site crash investigations and in-depth crash data collection for a period of 45 to 60 days on four 2-lane undivided highways and a 4-lane divided highway. Based on 76 crashes examined, researchers found a shift of crash pattern from head-on collisions on undivided 2- lane highways to front-rear collisions on divided 4-lane highways. This paper presents the methodology, analysis of crashes examined, and the critical safety problems identified for greater consideration in future highway development projects. This paper also highlights the need and significance of in-depth crash investigations to understand local traffic conditions and problems in India.
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.
Accidents with vulnerable road users require special attention within the road safety work because these accidents are often accompanied with severe injuries. Thus In 2006 at least 6200 Powered Two Wheeler (PTW) riders were killed in road crashes in the EU 25 representing 16% of the total number of road deaths while accounting for only 2% of the total kilometers driven. For the prevention of accidents with VRU above all the knowledge of the causes of the accidents is of special importance. This study is based on the methodology of the German In-Depth Accident Study GIDAS. Within GIDAS extensive data on various fields of accidentology are collected on-scene from road traffic accidents with injuries in the Hannover and Dresden area. Using a well defined sample plan the collected data is highly representative to the whole German situation (Brühning et al, Otte et al). The need of in-depth accident causation data in accident research led to the development of a special tool for the collection of such data called ACASS (Accident Causation Analysis with Seven Steps), which was implemented in the GIDAS methodology in 2008 and described by Otte in 2009.
There is a need for detecting characteristics of pedestrian movement before car-pedestrian collisions to trigger a fully reversible pedestrian protection system. For this purpose, a pedestrian sensor system has been developed. In order to evaluate the effectiveness of the sensor system, the in-depth knowledge of car-pedestrian impact scenarios is needed. This study aims at the evaluation of the sensor system. The accident data are selected from the STRADA database. The accident scenarios available in this database were evaluated and the knowledge of the most common scenarios was developed in terms of the pedestrian trajectory, the pedestrian speed, the car trajectory, the car velocity, etc. A mathematical model was then established to evaluate the sensor system with different detective angles. It was found that in order to detect all the pedestrians in the most common scenarios on time the sensor detective angle must be kept larger than 60 degrees.
The overall purpose of the ASSESS project is to develop a relevant and standardised set of test and assessment methods and associated tools for integrated vehicle safety systems, primarily focussing on currently available pre-crash sensing systems. The first stage of the project was to define casualty relevant accident scenarios so that the test scenarios will be developed based on accident scenarios which currently result in the greatest injury outcome, measured by a combination of casualty severity and casualty frequency. The first analysis stage was completed using data from a range of accident databases, including those which were nationally representative (STATS19, UK and STRADA, SE) and in-depth sources which provided more detailed parameters to characterise the accident scenarios (GIDAS, DE and OTS, UK). A common analysis method was developed in order to compare the data from these different sources, and while the data sets were not completely compatible, the majority of the data was aligned in such a way that allowed a useful comparison to be made. As the ASSESS project focuses on pre-crash sensing systems fitted to passenger cars, the data selected for the analysis was "injury accidents which involved at least one passenger car". The accident data analysis yielded the following ranked list of most relevant accident scenarios: Rank Accident scenario 1 Driving accident - single vehicle loss of control 2 Accidents in longitudinal traffic (same and opposite directions) 3 Accidents with turning vehicle(s) or crossing paths in junctions 4 Accidents involving pedestrians The ranked list highlights the relatively large role played by "accidents in longitudinal traffic", and "accidents with turning vehicle(s) or crossing paths in junctions" (the second and third most prevalent accident scenarios, respectively). The pre-crash systems addressed in ASSESS propose to yield beneficial safety outcomes with specific regard to these accident scenarios. This indicates that the ASSESS project is highly relevant to the current casualty crash problem. In the second stage of the analysis a selection of these accident scenarios were analysed further to define the accident parameters at a more detailed level .This paper describes the analysis approach and results from the first analysis stage.
Nowadays human-created systems are increasing in complexity due to the interaction of humans and technology. Especially road traffic systems are composed of multitudinous resources (e.g. personnel, vehicles, organizations, etc.), which make it even harder to anticipate the positive and negative effects on safety. One key in achieving a significant reduction of fatalities is seen in driver assistant systems counterbalancing the lack of drivers' capabilities. But the actual outcome of implementing these sophisticated technologies especially on influencing driver's capabilities are yet unknown. Latest research exemplifies an increase of reaction times of drivers in case of dysfunctional driver assistant systems. This research paper applies STAMP/STPA (STAMP = systems-theoretic accident model and processes; STPA = systems-theoretic process analysis) to the German automobile traffic system focusing on the effects of driver assistant systems on drivers. By doing so, the potential hazards caused by technology can be identified.
In general the passive safety capability is much greater in newer versus older cars due to the stiff compartment preventing intrusion in severe collisions. However, the stiffer structure which increases the deceleration can lead to a change in injury patterns. In order to analyse possible injury mechanisms for thoracic and lumbar spine injuries, data from the German Inâ€Depth Accident Study (GIDAS) were used in this study. A twoâ€step approach of statistical and caseâ€byâ€case analysis was applied for this investigation. In total 4,289 collisions were selected involving 8,844 vehicles, 5,765 injured persons and 9,468 coded injuries. Thoracic and lumbar spine injuries such as burst, compression or dislocation fractures as well as soft tissue injuries were found to occur in frontal impacts even without intrusion to the passenger compartment. If a MAIS 2+ injury occurred, in 15% of the cases a thoracic and/or lumbar spine injury is included. Considering AIS 2+ thoracic and lumbar spine, most injuries were fractures and occurred in the lumbar spine area. From the case by case analyses it can be concluded that lumbar spine fractures occur in accidents without the engagement of longitudinals, lateral loading to the occupant and/or very severe accidents with MAIS being much higher than the spine AIS.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.