Research On Regional Coordination Control Of Urban Traffic Network Based On MFD And MPC

With the expansion of the city scale and the increase of the population,the existing traffic signal control timing schemes are gradually unable to meet people's travel requirements.The urban congestion problem is becoming more and more serious.Therefore,how to use the existing urban traffic network control signal device to alleviate traffic congestion is the focus of current urban traffic control research.Complexity and non-linearity are inherent attributes of large-scale urban traffic network.Therefore,the core of traffic control problem are how to establish a traffic flow model,how to design a control system,and how to implement a control strategy.In this thesis,a hierarchical-coordinated control architecture based on S model is studied to solve the signal timing optimization problem of large-scale urban traffic network.Firstly,the shape and scattering of the macroscopic fundamental diagram in different traffic flow scenarios are verified by floating car data of Wangjing traffic network in Beijing,which proves that the traffic density in Wangjing area is heterogeneous.Secondly,an improved Newman fast algorithm based on vehicle density is proposed.It realizes the division of the heterogeneous traffic network.In the process of division,the vehicle density is used as the correlation model of intersections,and then the Newman fast algorithm is used for community detection and division.When merging each sub-network,the concept of regional contribution degree is introduced,and the sub-networks with small regional contribution degree and connected are merged.The improved algorithm saves traversal time of greedy algorithm,then improves the efficiency of partitioning algorithm.According to macroscopic fundamental diagram,it is shown that sub-network is homogeneous.Thirdly,a hierarchical-coordinated predictive control algorithm based on S model is studied.Compared with the Store-and-Forward model,the S predictive model adds some factors such as queue length and downstream capacity.So the predictive model becomes more accurate.The hierarchical-coordinated control architecture achieves the coordinated control between the various regions through the iteration of the coordinated factors.In the end,the goal of the timing schemes for all intersections in the entire traffic network is achieved.Finally,simulation experiments of studied algorithms in this thesis are implemented.Comparing with centralized control and timing control,the experiments show that the hierarchical-coordinated control strategy can ensure the optimization performance while reducing the computational time complexity.Therefore,for complex traffic systems,hierarchical-coordinated control is more feasible than centralized control.In this thesis,there are 30 figures,9 tables and 47 references.