Overview of the identification of traffic accident-prone locations driven by big data

Effective identification of traffic accident-prone points can reduce accident risks and eliminate safety hazards.This paper first systematically compares the research in Chinese and foreign literature,and proposes three types of identification indicators,namely absolute,relative and comprehensive,according to different reference standards.According to the evaluation indicators and modelling methods,the current status of research and problems in identification theory and methods are systematically summarised in terms of mathematical statistics,cluster analysis,machine learning and conflict technology.The study shows that the foreign literature focuses on the innovation of data and indicators and changes from accident point safety management to road network safety management,while the research in Chinese literature focuses on the integration of multiple identification methods and theoretical innovation.Driven by big data,the identification of traffic accident-prone points has been further developed at the meso-micro scale.Morphological image processing methods are widely used,combined with GIS platforms,to accurately mine the spatial attributes and correlations of accidents.Also,considering the spatial and temporal distribution of accidents,the identification results are also transformed from regions to specific road sections and points to achieve more accurate identification.

事故倾向性儿童意外伤害影响因素及干预策略的研究进展

意外伤害是危害儿童身心健康的重大公共卫生问题,在所有儿童中,事故倾向性儿童占2%左右,意外伤害一旦发生,将会导致发育不良、残疾甚至死亡等严重后果。因此,为了减少因意外伤害带来的致残、致伤、致亡,本文对该类人群的相关文献进行了回顾,并对其意外伤害发生的影响因素及干预策略进行综述,旨在加深对此人群的认识,以期为今后制定相应的干预策略提供依据,从而减少该类儿童意外伤害的发生。