Analysis on the association between driver's macroscopic characteristics and accident type of urban traffic accidents

Data mining technology is used to analyze the association between driver's macroscopic characteristics and accident types of drivers of urban traffic accidents. Based on the correlation between microscopic characteristics (such as physiology and psychology of the driver and macro characteristics (such as sex, age and driving age), the statistic values of driver sex, age and driving characteristics of road in traffic accidents are taken as the comparison sequences, and the types of traffic accidents as the reference sequence. Simultaneously, the gray relational model of the driver's accident and the accident type is established. By analyzing the quantified results of the gray incidence matrix, evaluated the different characteristics of the transport drivers for the influence of the accident types, and a reference for prevention of traffic accidents is provided effectively.