Research On Collaborative Current Limiting Of Urban Rail Transit Network Based On Data-driven

With the planning and construction of urban rail transit in many cities,the mileage and density of urban rail transit continues to increase,and the trend of networked operations becomes more and more obvious.At the same time,the challenges of complex operating organizations,heavy hub loads,and high passenger flow intensity have gradually become important issues to be faced and solved.In order to alleviate the passenger flow pressure and congestion of the urban rail transit network and ensure the safety of passengers,this paper studies the method of formulating the urban rail transit network cooperative current limiting scheme under the given urban rail transit network capacity allocation strategy,and uses data mining method to evaluate the status of the urban rail transit network and the station.Case study of Guangzhou urban rail transit network was selected.The main work is as follows:(1)In-depth analysis of the urban rail transit network cooperative current limiting problem from the principle,influencing factors and measures of urban rail transit network cooperative current limiting,determine the three elements of the urban rail transit network cooperative current limiting scheme,and propose the basic process of quantitative formulation and the methods applied by each process of the urban rail transit network cooperative current limiting.(2)Construct the state evaluation index of the urban rail transit network and the station,that is,the full load rate distribution entropy,the high full load rate interval ratio,the station platform congestion degree and the average train arrival full load rate.On this basis,use the Gaussian mixture model clustering method based on K-means classifies the evaluation indexes of the urban rail transit network and the station.The method can automatically determine the optimal number of grades.What's more,the K nearest neighbor classification method is used to evaluate the operation status of the urban rail transit network and the station,and then determine the current limit period and the critical current limit station of the urban rail transit network coordination to reduce the research scope of the coordinated current limiting scheme.Considering the synergy between stations,the correlation degree between the key current-limit stations is analyzed,the key current-limit stations are divided into different areas,and then the stations in the same area are cooperatively restricted.(3)Establish a collaborative current limiting model of the urban rail transit network based on the current limit period and the critical current limit station identified,aiming at maximizing the number of service personnel at each station and minimizing the average number of stations at each station,and Constraints are imposed on passenger flow demand,inbound process,current limiting process,platform capability,train capacity,boarding and unloading process,and station coordination.Using the Q-learning learning algorithm to solve the cooperative current-limiting model can solve the problem that the current-limiting model is large and the traditional method can't solve it.According to the result,the collaborative network-based flow limitation scheme is quantitatively determined,that is,the specific current-limit station and current limiting intensity are determined.The purpose of alleviating the congestion of the urban rail transit network can be achieved.(4)Taking the early peak Guangzhou urban rail transit network as an example,based on the simulation data,the operation status of Guangzhou urban rail transit network and station is automatically identified,and the urban rail transit network cooperative current limiting method is used to learn the urban rail transit network cooperative current limiting scheme Comparing with the existing network current limiting method in "Guangzhou Metro Network Operation Status Evaluation and Guidance System" The results show that the method studied in this paper is better than the existing method,which can effectively alleviate the congestion of the urban rail transit network and improve the operational organization level of the urban rail transit network.