Clustering of Freight Vehicle Driving Behavior Based on Vehicle Networking Data Mining

[Purpose/meaning] The massive information of car under the network environment is of special significance and value to analyze the characteristic of the freight vehicle driving. Through mining vehicle speed, acceleration and other driving data is advantageous to help research vehicle drivers driving behavior and to standard the driver’s driving behavior, and realize the intelligent management of the vehicle. [Methods/processes] In this paper, the part of freight vehicles operating within the bounds of Hebei province as the research object to obtain the characteristic parameters of vehicle driver’s driving behavior, and using data mining method based on factor analysis to convert the parameters as indicators of the K-Means clustering method to analyze driving behavior. [Results/conclusions] According to the analysis results, dangerous driving behavior in the process of freight vehicles on the road exists and there is a certain effect for road transport safety, but they are all very few. By studying the characteristic parameters of velocity and acceleration of the vehicle can better response freight vehicles in operation in the process of driving behavior, and it contributes to the intelligent vehicle management.