Research on Data Resource Classification for Intelligent Highway Scenarios

In the realm of intelligent highways, vast amounts of data are generated from the activities involving with road design, construction, and management. These data require comprehensive collection, organization, and reconfiguration in order to form standardized and cohesive datasets that can be classified and graded for applications in intelligent scenarios, such as advanced driver assistance and intelligent road maintenance. The objective of this paper is to build a dataset that is replete with professional and detailed information for the applications of intelligent highway scenarios. For this purpose, an unified data resource directory is established, and highway data are classified through digital processing of various road engineering periods, including survey, design, construction, and maintenance. In the directory, each data element is accompanied by detailed information, including the name, source, content, format, etc. This information is more detailed and comprehensive than that of other existing information resource standards. Furthermore, a new type of data called “virtual space-time information” has been investigated and gathered. This type of data is specific originating from intelligent highway technical scenarios and is used to combine the dynamic and static data generated from massive traffic infrastructures and traffic operation status. By leveraging artificial intelligence, big data, cloud computing, and other technologies to simulate highway information, the data resource can ultimately serve as the foundation for various application scenarios such as construction supervision, maintenance analysis, and decision-making. Based on the aforementioned work, a method for classifying data into detailed categories has been devised, enabling different types of highway data to be categorized into groups and form an unified data resource. This resource can serve as a foundation and crucial support for intelligent highways.