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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.
It is very important for Automotive OEMs to get feedback on their product performance on real roads for continuous improvement. Every OEM has a way of collecting this feedback for various performance parameters. Systematic accident research is a way to generate the information related to safety performance of the vehicle. In India, while there is a large amount of data related to the accidents, it is found this data is aimed at understanding the gross statistics and not directly useful for technology development. This paper explains learnings from a pilot study carried out in collaboration with an Emergency Medical Services provider on one of the expressways (motorways). This pilot study has resulted in development of working model that could now be scaled up at for wider application. The paper also presents some of the important observations based on the data collected.
The objective of the study is to measure the risk of pedestrian and bicyclist in urban traffic through an analysis of real-world accident data. The kinematics and injury mechanisms for both pedestrian and bicyclists are investigated to find the correlation of injury risks with injury related parameters. For this purpose, firstly 338 cases are selected as a sample from an IVAC accident database based on the In-depth Investigation of Vehicle Accident in Changsha of China. A statistic measurement of the fatality and serious injury risks with respect to impact speed was carried out by logistic regression analysis. Secondly, 12 pedestrian and 12 bicyclist accidents were further selected for reconstruction with MADYMO program. A comparative analysis was conducted based on the results from accident analysis and computer reconstructions for the injury risk, head impact conditions and dynamic response of pedestrians and bicyclists. The results indicate that bicyclists suffered lower risks of severe injuries and fatalities compared with pedestrians. The risks of AIS 3+ injury and fatality are 50% for pedestrians at impact speeds of 53.2 km/h and 63.3 km/h, respectively, while that for bicyclists at 62.5 km/h and 71.1 km/h, respectively. The findings could have a contribution to get a better understanding of pedestrians" and bicyclists" exposures in urban traffic in China, and provide background knowledge to generate strategies for pedestrian protection.