Research On Dynamic Coordinated Control Method Of Arterial Traffic Signal Based On Multi-source Data

With the improvement of Chinese economic level and construction process,the number of motor vehicles has also shown a trend of continuous growth.More and more residents regard private cars as the preferred means of transportation,which leads to the increase of urban road vehicles and the decrease of traffic capacity.In particular,the number of vehicles entering and leaving the city during morning and evening peaks often exceeds road load,and the congestion situation is not optimistic.As the vein of the road network,the arterial road undertakes the traffic task of the main traffic of the city and plays an important role in the urban road.Among them,the intersection is the node of many arterial roads in the city,and its traffic condition will have a significant impact on whether the arterial road can smoothly pass.Coordination control of arterial traffic signals is an important means of urban traffic control.In order to reduce arterial road system delays and improve road traffic capacity,traffic coordinated control is implemented by connecting several adjacent intersections in a certain way.Nowadays,the signal control system mainly collects traffic data through the induction coil,microwave,geomagnetism,video and floating car detection technology.In practical application,the data used usually obtain from only one kind of source,the effect of signal control is easily affected by the accuracy of data.In recent years,with the rapid development of data collection,Internet,Internet of things,big data,cloud computing and other technologies,traffic data sources have been more extensive and diverse,which provides a new way for the research of arterial traffic signal coordinated control.Therefore,this paper studies a complete set of dynamic coordination control methods for arterial traffic signals based on multi-source data.The main work is as follows:Firstly,the processing method of multi-source traffic data is constructed.Valid information is filtered through data preprocessing,and the wrong data are eliminated or repaired.For traffic data that can only obtain by a single detector,that should be extracted and processed separately.For traffic data collected from multiple sources,BP neural network is used to fuse the data.Secondly,discriminated arterial traffic status based on multi-source data.Based on the analysis of intersections and sections,the corresponding state discriminant parameters are selected,and the arterial traffic state is divided into two categories: unsaturated,saturated and over-saturated.Traffic states are distinguished by using the index weighted fuzzy clustering method.Thirdly,according to different traffic characteristics under unsaturated,saturated and over-saturated conditions,the corresponding control strategies are determined.The maximum green wave band is taken as the objective in the unsaturated state,and the minimum delay is taken as the objective to design the coordinated control scheme of arterial traffic signals in the saturated and over-saturated state.The deficiencies of the maximum green wave band and the minimum delay model in the existing research are improved.Fourthly,a new evaluation method of arterial traffic coordinated control scheme is proposed to realize the dynamic evaluation of the design scheme.Based on the evaluation results of arterial traffic coordinated control scheme,whether the signal timing parameters need to be optimized and updated are determined.In order to ensure smooth and stable operation of arterial traffic flow,the calculation method of transition between new and old schemes is given.Finally,in order to verify the effectiveness of the proposed arterial traffic coordinated control method and the improved model,this paper carried out actual case analysis and traffic modeling simulation.This research determined the optimum renewal interval of dynamic coordinated control of arterial traffic signals,evaluated the accuracy of multi-source data fusion,analyzed the clustering results under different traffic conditions,and compared the operation effect of arterial road vehicles under the control of optimization scheme and current scheme.The results show that dynamic arterial traffic signals coordinated control method based on multi-source data can effectively reduce intersection delay,queue length and the number of parking,and has a good effect on alleviating arterial traffic congestion and improving traffic efficiency.This paper discriminates traffic flow status of arterial road based on the method of multi-source data fusion,determines the corresponding signal coordination control strategy of different traffic state,implements the target-oriented traffic signal coordinated control of arterial road,and achieves certain results.The method in this paper provides a new idea for the research of arterial traffic signal coordinated control.And the follow-up research will further explore how to establish a more real-time and dynamic evaluation feedback mechanism by using artificial intelligent algorithms.