| As the urbanization process accelerates,the urban area continues to expand,and the distribution spans of urban residential areas,working areas,and functional areas increase,and the resulting characteristics of tidal traffic travel become more obvious.In many urban intersections,traffic flow in different directions is obviously unbalanced in different periods,which leads to frequent node congestion caused by imbalance between flow direction and supply.When traffic flow is dense and traffic demand for each turn fluctuates greatly,the effect is not obvious only by the traditional traffic signal timing optimization.Directional traffic can be used to change the lane division,combining with signal timing adjustment,to reasonable allocation of intersection space and time resources,and ensure the efficiency of intersections in different states.This article takes the flow to the intersection of supply and demand imbalance as the research object,facilitate artificial neural network technology to establish short-term traffic flow prediction models.By analyzing the differently efficiency of directional traffic,research lane function control strategies for two ways.According to the effect of two control methods of variable traffic under different traffic conditions on the improvement of intersection operation efficiency,establishing intelligent traffic control methods,and realized to dynamic optimization of space-time resources at intersections.Firstly,the multi-source data is used to study the short-time traffic flow prediction model at intersections.Based on the intelligent technology equipment to get the basic traffic data,the NARX neural network model be used to predict traffic flow.By analyzing the error of the model and combining the characteristics,to established the GA-NARX neural network mode.The validity of the model is verified using actual data.Secondly,the influence of the changing traffic on the operation status of the intersection is analyzed.Taking the actual intersection of Zhangdian District in Zibo City as an example,the theoretical analysis of the impact of the implementation of variable guide lanes and reverse variable lanes on the intersection's capacity,saturation flow rate,saturation,signal phase sequence and program,etc.Thirdly,established a coordinated optimization model for the function of traffic lane change and signal timing.(1)Taking the optimal traffic capacity and the minimum vehicle delay as the optimization goals,a collaborative optimization model of space-time resources with variable guidance lanes was established.(2)Based on the efficiency and safety of intersections,a collaborative optimization model of reverse variable lane space-time resources was established.(3)Through quantitative analysis,Through quantitative analysis,the relationship between the two control methods of changing traffic under arbitrary traffic conditions and the signal control was studied.It also describes the control limits of the two control methods for traffic change,and establishes a comprehensive intelligent control method for traffic change according to the benefit value of the impact on the operation of the intersection under different control schemes.Finally,Taking the intersection of Liu-quan Road and Hua-guang Road in Zhangdian District,Zibo City as an example for practical verification.Simulation results show that,compared with the conventional control scheme,after adopting the integrated intelligent traffic control method for traffic change researched in this paper,the vehicle delays of the early peak,flat peak and evening peak of the intersection decreased by 19.32%,29.72% and 32.36%.It proves that the intelligent change control method proposed in this paper can dynamically adjust the spatio-temporal resources of the intersection according to the change of the flow direction demand of the intersection,so that the intersection can achieve the cooperative optimal control effect,and effectively improve the operation efficiency of the intersection... |
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