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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.
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.
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.
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.
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.
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.
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 the accident scenario of powered two-wheelers on the basis of real-world accidents
(2013)
For the first time since 20 years the German national statistics of traffic accidents revealed an increasing number of fatalities and seriously injured persons in 2011. This negative development was especially caused by increasing numbers in all groups of vulnerable road users (VRU). Furthermore, the comparison of fatality reduction rates between several categories of road users shows that persons on motorcycles show the worst performance over years. Although every second fatality in German traffic accidents is still a car occupant, users of PTW make up more than 20% in the meantime. Assuming further improvements in the field of occupant protection this trend will continue. For that reason, a study on the basis of real-world accidents was conducted to describe the accident scenario involving motorcycles and to identify the reasons of the above-described fact. Approximately 1.800 motorcycle accidents out of GIDAS database were used for the analyses. The first part of the study deals with the question how representative the GIDAS database is for the German motorcycle accident scenario. Afterwards, detailed descriptive statistics on motorcycle accidents were presented considering numerous parameters about the accident scene, environmental influences, vehicle information, individual characteristics, interview data, injury severity and injury causation. One important point is the identification of the most frequent critical situations that are typical for motorcycle accidents. Furthermore, a special focus was on accident causation. Finally, conspicuous facts out of the analysis are emphasized. All in all, the study gives a comprehensive overview about the German motorcycle accident scenario. One the one hand, the use of weighted GIDAS data allows representative and robust statements on the basis of large case numbers; on the other hand highly detailed conclusions can be drawn. The results of the study help to understand the particularities of motorcycle accidents and provide approaches for further improvements in the field of PTW safety.
From literature well-known analyzes on risks, hazards and causes of accidents of older drivers are amended by the present study in which a comparison of the specific features of accident causes of older car drivers (older than 60 years) and of younger car drivers (under 25 years) is conducted. Mainly the question is pursued if specific errors, mistakes and lapses are predominant in the two different age groups. The analysis system ACAS (Accident Causation Analysis System) used hereby consists of a sequential system of accident causation factors from the human, the technical and the infrastructural field, whereupon for this study the influence of the human features on the accident development in two different age groups is of interest. ACAS is both an accident model and an analysis and classification system, which describes the human participation factors of an accident and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. In five steps (categories) of a logical and temporal sequence the hierarchical system makes human functions and processes as determinants of accident causes identifiable. The methodology specifically focuses on the use in so-called "In-Depth" and "On-Scene" investigation studies. With the help of the system for each accident participant one or more of five hypotheses of human cause factors are formed and then specified by appropriate verification criteria. These hypotheses in turn are further specified by indicators in such manner that the coding of the causation factors by a code system meets the needs of database processing and are accessible to a quantitative data analysis. The first results of the descriptive comparison of the two age groups concern mainly differences in the functional levels "information admission/perception" (where the elderly drivers have more difficulties than the young ones) and "information processing/evaluation" (where the younger drivers show more problems). Concerning the cognitive function of "planning" the group of younger drivers seems to be more often involved in an accident because of excessive speed.
The effect of fatigue on driving has been compared to the effect of alcohol impairment in both driver performance and crash studies. However are crash characteristics and causation mechanisms similar in crashes involving fatigue to those involving alcohol when studied in the real world? This has been explored by examining data held in the EC project SafetyNet Accident Causation Database. Causation data was recorded using the SafetyNet Accident Causation System (SNACS). The focus was on Cars/MPV crashes and drivers assigned the SNACS code Alcohol or Fatigue. The Alcohol group included 44 drivers and the Fatigue group included 47. "Incorrect direction" was a frequently occurring critical event in both the Alcohol and Fatigue groups. The Alcohol group had more contributory factors related to decision making and the Fatigue group had more contributory factors relating to incorrect observations. This analysis does not allow for generalised statements about the significance of the similarities and differences between crashes involving alcohol and fatigue, however the observed differences do suggest that attempts to quantify the effect of fatigue by using levels of alcohol impairment as a benchmark should be done with care.