Expressway traveler classification algorithm based on toll data

Traveler classification is of practical significance for the operation and management of highways. In order to refine the analysis of vehicle travel distribution characteristics, promote effective measures to use data for traffic theory research, and provide better management for highways, this paper proposes a classification model using highway toll data in Shandong Province. This paper combines big data to analyze the spatial and temporal distribution characteristics of travel users. Seven indicators were constructed from four dimensions: traveler's perspective, travel time, travel intensity, and travel space. Then we use K-means++ algorithm to cluster the full sample of travelers. Travelers are divided into five categories, which are commuter travelers, life travelers, work travelers, sporadic travelers and other travelers. The results show that the proposed model can effectively classify highway travelers, and the distribution of travelers' characteristics varies significantly among categories, which can provide reasonable suggestions for highway management.