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Expressway travel time prediction model based on multi-source data fusion

Expressway travel time prediction is an important means for managers to manage and make decisions, guide them to choose a reasonable travel path, and improve expressway traffic efficiency. This paper organizes and analyzes expressway ETC gantry system data, toll station data, integrated transport information system data, video structured data such as data collection and analysis. On the basis of multi-source data fusion, this paper build the travel time prediction model based on extreme gradient boosting, and is verified using the actual data of a domestic expressway for verification and example analysis. According to the study, the accuracy of the constructed expressway travel time prediction algorithm is above 90%, with an average accuracy of 93.2%. It has high accuracy and reliability, and has high application value.