Prediction of the Technical Status of Highway Pavement Based on Charging Data

On the highway, the rapid growth of the freight transportation leads to a sharp increase in actual traffic loads, and then directly causes serious damage to the pavement. Considering pavement maintenance, it is necessary to study the relationship between the truck axle load and the damage of pavement so as to providing data for the highway pavement maintenance. In China, for transport vehicles on highways, they are generally charged by weight. Besides, the damage condition of pavement can be detected periodically by manual work or the rapid testing equipment. These two points provide basic data for the study of the relationship between axle load of highway trucks and the pavement damage. In this paper, first, extract standard axle load that can represent the traffic load and the technical status of the pavement that can represent road damage based on the data of the loading-based toll collection data and the pavement's technical status. Then, the machine-learning algorithm was used to study the relationship between the traffic load and the pavement damage to predict the technical status of the pavement.