The invention discloses a
traffic prediction method for Internet of Vehicles communication based on
machine learning, and the method comprises the steps: selecting eight types of data indexes by utilizing a
traffic speed database issued by a traffic
data platform, and completing the all-weather
traffic flow prediction through a
random forest algorithm after parameter optimization; exporting an
urban road vehicle
traffic scene in a certain place by utilizing the openstreetmap, obtaining traffic data, configuring a communication
simulation file, obtaining communication data, mixing the two kinds of data, and analyzing the relationship between the
traffic flow and the communication flow; exporting a road section selected by a traffic
data platform by utilizing openstreetmap, configuring a communication
simulation file, acquiring communication data, selecting nine types of related indexes from flow speed data and communication data released by the traffic
data platform, and performing communication flow prediction through a Bagging model. The method is good in generalization performance and high in accuracy, a reliable vehicle-mounted
communication analysis method can be provided for later-stage utilization of economic and efficient data distribution, and the
driving safety of vehicle users is enhanced.