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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.
A lack of representative European accident data to aid the development of safety policy, regulation and technological advancement is a major obstacle in the European Union. Data are needed to assess the performance of road and vehicle safety and is also needed to support the development of further actions by stakeholders. This short-paper describes the process of developing a data collection and analysis system designed to partly fill these gaps. A project team with members from 7 countries was set up to devise appropriate variable lists to collect fatal crash data under the following topic levels: accident, road environment, vehicle, and road user, using retrospective detailed police reports (n=1,300). The typical level of detail recorded was a minimum of 150 variables for each accident. The project will enable multidisciplinary information on the circumstances of fatal crashes to be interpreted to provide information on a range of causal factors and events surrounding the collisions.
Road safety is a major preoccupation of the European Commission and the road transport industry and depends on numerous significant factors. In order to improve road safety and to plan effective safety improvement actions for truck transport, we must first identify the problems to be addressed, i.e. what are the main causes of truck accidents. The ETAC project, initiated by the European Commission and the IRU, was launched in order to set up a heavy goods vehicle accident causation study across European countries to identify future actions which could contribute to the improvement of road safety. The results will be based on a detailed analysis of truck accident data collected in seven European countries according to a common methodology which has been elaborated through numerous national and European projects. This paper describes the common methodology used to collect the information on the scene of the accident and to analyse the data so that the reconstruction of the crash events may be carried out. CEESAR proposes a methodology using its experience gained from over 10 years of accident data collection. This methodology is based on an in-depth investigation of the parameters involved in-an accident and linked to the driver, the vehicle, the road and their environment. In-depth investigation requires accident investigator presence on the scene of the accident in order to collect volatile information such as marks on the road, weather conditions, visibility, state and equipment of the vehicle, driver interview. Later, passive and active information is gathered, either at the hospital for the driver, at the garage for the vehicle or on the spot for the road geometry. A reconstruction carried out with the help of specific software and the analysis of the data collected and calculated enables the identification of the main causes of the accident and the future actions to plan in order to improve road safety as regards truck traffic.