Traffic safety risk based group division and a difference analysis method and system: taking drivers and motor vehicles as objects, demarcating safety risks of the objects by using an ensemble learning algorithm and carrying out group division on the basis of the safety risks, and identifying salient difference indexes through a statistical approach; mining features of traffic participants from traffic behaviors thereof on the basis of the ensemble learning algorithm and demarcating safety risk degrees of said traffic participants, and in order to reduce data granularity of an analysis and determining program, dividing, according to the risk degrees, into a plurality of target groups having different safety levels; in order to overcome the problem that the ensemble learning algorithm lacks explanation during safety risk demarcation, accurately testing and identifying salient difference indexes among groups by using Fisher, thus accurately describing features of groups having various risk levels and providing data support for active traffic safety management.
TRAFFIC SAFETY RISK BASED GROUP DIVISION AND DIFFERENCE ANALYSIS METHOD AND SYSTEM