Divided lane traffic flow proportion prediction method based on Kalman filtering

• Main Authors: LI BING, CHEN DONGNI, YIN DEPENG, CHENG WEI, LI LISHAN
• Format: Patent
• Language: Chinese; English
• Published: 22.01.2019
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SIGNALLING; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR; TRAFFIC CONTROL SYSTEMS

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 b