Synergistic Optimization Study Of Urban Rail Transit Train Stop-hopping And Passenger Flow Control

With the increasingly sharp contradiction between supply and demand of urban rail transport,the phenomenon of highly crowded platforms and passengers being stranded on platforms during morning and evening rush hours,holidays and large events is common,which not only threatens the safe operation of urban rail transport but also causes great inconvenience to passengers.In order to solve this problem,many cities have introduced regular flow restriction measures.However,on the one hand,as most of the current flow restriction measures are implemented based on experience,on the other hand,regulating only from a single perspective of supply or demand is no longer able to significantly alleviate this contradiction.Therefore,this paper proposes a synergistic optimisation of urban rail transit train hopping and passenger flow control from both supply and demand perspectives.The thesis begins with a study and analysis of the spatial and temporal characteristics of urban rail traffic,the characteristics of large passenger flows,conventional passenger flow control measures and the optimisation of train running schemes.Secondly,the topology of the rail network is modelled,the definition of effective paths and search algorithms are investigated,the behaviour of passengers in choosing their travel paths is analysed,transfer time amplification coefficients and transfer number penalty coefficients are introduced in the calculation of generalised travel costs,the relative difference in path costs is used instead of the absolute difference to improve the Logit model and solve for path selection probabilities,after which the road network OD combined with interchange stations is transformed into line OD to obtain the passenger inbound flow rate at each station and the proportion of passengers going to other stations.Based on this data,a collaborative optimisation model of train hopping and passenger flow control for urban rail transport is established.A series of constraints are applied to train hopping and passenger flow control to establish a mixed integer non-linear optimisation model with the shortest total train running time,the lowest total number of stranded passengers and the lowest maximum number of stranded passengers at a station as the objective functions.Finally,taking the Xi’an Metro as an example,the Xi’an city weekday morning peak OD data and train operation map are used as the data base to carry out network-wide passenger travel path selection,and the selection results are substituted into the collaborative optimization model,which is solved by calling gurobi with MATLAB to obtain the model results,and finally the data of Xi’an Metro Line 2 in the direction of Xi’an bei-Weiqu nan are used for comparison and validation.The results show that the synergistic optimisation model of train hopping and passenger flow control can reduce the train running time,total number of stranded passengers and maximum number of stranded passengers with a small loss of passenger traffic,dispersing the concentrated stranded passengers at a single station to the rest of the stations and greatly reducing passenger congestion at key stations.Different coefficients are adopted in the objective function to obtain different optimisation results.In practice,the operator can take the coefficients according to the actual needs,and the model can provide theoretical support for the operation of urban railways.