Multi-ramp cooperative control method based on model predication control

Abstract

The invention discloses a multi-ramp cooperative control method based on model predication control. The multi-ramp cooperative control method comprises the following steps: 1) carrying out sub-regiondivision on a multi-ramp road network; 2) drawing a macroscopic fundamental diagram of each sub-region, and determining the quantity of vehicles corresponding to an optimal operation state of each sub-region; 3) establishing an upper-layer principal line correlated multi-ramp cooperative control model; 4) establishing the model predication control of a lower-layer subsystem; 4) solving the model.According to the method disclosed by the invention, the quantity of residual vehicles in each sub-region is used as a performance index to establish the cooperative control model to solve a control rule of each ramp; furthermore, a signal control scheme of each ramp is solved; meanwhile, a model predication control strategy is combined, so that the ramp control effect is better and traffic flow distribution of all the ramps is more uniform.

Description

technical field [0001] The invention relates to the field of ramp cooperative control, in particular to a multi-ramp cooperative control method based on model predictive control. Background technique [0002] With the advent of the new era in the new century, the rapid development of my country's urban social economy has led to the continuous expansion of the city scale, urban development has entered a new period of urban-rural integration, and the scale of the urban road network has also continued to expand. Compared with ordinary roads, the rapid transit channel has the advantages of being fast, smooth, and comfortable. Therefore, most cities have begun to vigorously build expressways to share the traffic volume of urban arterial roads in order to alleviate traffic congestion on urban central roads. However, with traffic demand The continuous expansion of the urban expressway system, especially the substantial increase in intercity and suburban traffic flow, reduces the over...

AI Technical Summary

Problems solved by technology

Jiang Zifeng et al. proposed the joint adjustment model of the on-ramp and the diversion model of the off-ramp, and then used the conservation equation, speed equation and steady-state speed-density equation in the META model to coordinate the two models to realize the coordinated control of multi-ramps; Zhu et al. improved the network load layer in the multi-ramp hierarchical control structure of the expressway, and added the OD matrix prediction based on the Kalman filter method to realize the prediction of the total demand and the length of the ramp queue. Prediction data realizes multi-ramp coordinated control; K. Bogenberger and A.D.May conducted some research on ramp adaptive cooperative control strategy, and explained the application of ANN in ramp cooperative control, and proposed a dynamic layered online simulation and adaptive fuzzy control two research directions; Li Shuhong et al. established a multi-ramp coordinated control model based on a two-level programming model from the road network level, but the defect of this model is that the set impedance strictly increases with the flow rate, and queuing is not considered A.Kotsialos et al. applied AMOC to multi-ramp coordinated control of urban rapid lane change, and used simulation to analyze control efficiency and fairness in different scenarios; I.Papamichail et al. considered multi-ramp hierarchical Control structure, combined with heuristic algorithm, proposed a multi-ramp cooperative control strategy and method based on heuristic algorithm and hierarchical structure; Q.Meng et al. researched multi-ramp coordinated control from the perspective of fairness, based on Pareto Optimum theory and improved cellular transport model established a multi-objective ramp coordination control model; Li Wei et al. established a traffic flow model of express road network based on dynamic graph hybrid automata and cellular transport model to analyze the traffic flow of the system. Balance state set, and then propose a distributed ramp coordination control method, the control goal of this method is to make the system state reach a certain equilibrium state as much as possible; Zhu Jiong proposed a dynamic coordination control method for multi-entry ramps under congested conditions, In this method, the maximum flow rate of the system and the minimum average waiting time of on-ramp vehicles are the control objectives, and the optimal adjustment rate corresponding to each on-ramp under different control cycles is discussed; Xiong Jian proposes a multi-ramp coordinated control problem for expressways. A new genetic ant colony hybrid algorithm was used to construct a multi-ramp coordinated control model, and the controller parameters of each ramp were optimized through this model to achieve the purpose of coordinating and optimizing the adjustment rate of multi-ramps; Niu Zhonghai et al. proposed different control ranges for different ramps. Ramp control mode, research on ramp control from two levels of local control and road network global control

[0004] To sum up, in the research of multi-ramp control, the research type of multi-ramp cooperative control related to one-way main line has received special attention. In view of the complex problem of multi-ramp cooperative control system, the two main methods are hierarchical control and distributed control. They all belong to the research field of real-time traffic control, but they are not involved in predictive control, especially the predictive control based on rolling time domain. In addition, in the past, the ramp control law was finally obtained by solving the ramp control law, which could not be directly implemented.

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