Overspeed events multiple sections research based on clustering algorithm

Aim at the problem of road transportation security, this paper uses a clustering method to deal with the vehicle data collected by GPS equipment. From the GPS real-time supervisory data, we could explore the locations with overspeed density higher than the threshold and create the overspeed points cluster at maximum density value. Those sections with density higher than this maximum value are overspeed events multiple sections. The application of adjacency list replaced R*- Tree simplifies the establishment of data structure and reduces the memory footprint. Then use the clustering result to get the related information of the key monitoring vehicles and driver. The experiment results demonstrate the validity of our approach. The comprehensive research results enable department of transportation management and transportation enterprises to achieve safe supervision.