Divided lane traffic flow proportion prediction method based on Kalman filtering

Abstract

The invention discloses a divided lane traffic flow proportion prediction method based on Kalman filtering, and belongs to the technical field of transportation. Recursive cyclicity of the Kalman filtering theory is used, when the traffic flow proportion of a lane i is predicted, traffic flow proportion data of all lanes in the first three moments are called, the defect that a previous method onlyuses the proportion of traffic flow in the first three moments of the lane i when predicting the proportion of the traffic flow in the lane i is overcome, historical data is fully used, and the prediction precision is effectively improved. R language programming is used for obtaining an estimated initial value of a state vector by a at least square method, rapid convergence in the filtering process is facilitated, the deficiency of given initial parameters in the previous method is remedied, and the reliability of a prediction result is higher. According to the divided lane traffic flow proportion prediction method based on Kalman filtering, the process is simple, calculation is facilitated, and the operability is higher.

Description

technical field The invention relates to a method for predicting the proportion of traffic flow in lanes based on Kalman filtering, which belongs to the technical field of traffic. Background technique With the continuous development of the urban economy and the sharp increase in the number of cars, intelligent traffic management and road network dynamic optimization control are indispensable to the real-time monitoring and prediction of the traffic flow ratio of each lane at the intersection, and the prediction of the traffic flow ratio of the lanes based on Kalman filter The method can effectively predict the traffic flow ratio of each lane according to the historical road traffic data, so as to provide strong support for traffic control, improve traffic efficiency, alleviate traffic congestion, and realize traffic optimization control strategies. In the existing traffic flow prediction method based on Kalman filter, only the historical data of lane i is considered when pr...

AI Technical Summary

Problems solved by technology

In order to overcome the shortage of historical data call in the traditional traffic flow ratio prediction and the defect of using the initial value estimated by the given state vector in the Kalman filter prediction, the present invention provides a lane-divided traffic flow ratio prediction method based on the Kalman filter

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