| Summary: | In order to improve the accuracy of traffic flow prediction,a time gear traffic flow prediction model (TGM) with multiple factors integration was proposed by combining the characteristics of urban road traffic.The model was divided into two modules for feature mining of traffic flow influencing factors.Module 1 extracted the characteristic information of weather factors by deeply analyzing the influence of weather factors.Module 2 imitated the relationship between rotating shaft and gears.The traffic flow of target roadway and its neighboring intersections were treated as the gear teeth.The model framework adopted the bidirectional gated recurrent unit (Bi-GRU) with attention mechanism in both forward and opposite directions.The results show that the TGM model is significantly better than many existing models.Compared with Bi-GRU model,TGM model improves the accuracy of traffic flow prediction of 5,15 and 25 min by 4.75%,6.37% and 6.73%,respectively.Therefore,TGM model can effectively improve the prediction accuracy of traffic flow,and has better medium and long-term traffic flow prediction ability.It can be helpful for traffic organization optimization and traffic flow theory research.
|
|---|