Research on intelligent traffic risk assessment method based on grey clustering

Nowadays, the data generated by expressway operation is large in scale and various in types. When analyzing expressway safety risk, the traditional methods are easily subject to the subjective limitations of analysts, as well as the limitations of experience or knowledge, making it impossible to accurately predict traffic risk, and the traditional attribution theory model cannot simultaneously process and analyze multiple heterogeneous data. The data warehouse and data mining technology based on big data drive can analyze the operation data of different ranges and regions in a unified way, mine the spatio-temporal distribution characteristics, improve the scientific utilization efficiency of traffic data resources, and improve the information service level for traffic safety and early warning. This paper starts with the characteristics of road traffic accident information collection data and the key problems of data analysis and application in China point, reduce the occurrence of road traffic accidents through multi angle and all-round grey clustering evaluation method analysis.