Research on Real-Time Traffic Condition Identification of Highways Based on Chinese BEIDOU Positioning Data

摘要

According to the existing research on the highway traffic processing models based on FCD (floating car data), researchers mostly use the traditional methods based on travel speed, and there is few research on features of vehicle running on complex road section of highways. Because a large number of vehicles run near the toll gate and service area of highways, or temporarily pull over on the roadside, it will seriously affect the accuracy of real-time traffic identification if the vehicles cannot be cleaned and eliminated effectively. In this article, we analyze the differences of positioning data between BEIDOU and GPS and discuss the features of vehicles running on the complex road section and pulling over temporarily on the roadside, setting up a recognition model for the vehicles by means of cluster analysis, and implemented data cleaning and data eliminating of the vehicles effectively. On the basis of the above work, we set up the real-time traffic identification model based on BEIDOU positioning data for highways and try to improve the identification accuracy.