Passenger Flow Propagation Modeling And Inflow Control Research Of Urban Rail Transit Network

With China's urbanization and the rapid development of urban rail transit,urban rail transit has increasingly become a crucial means of transportation for urban daily travels.Peak-hour passenger congestion and its propagation has become a major problem,however,threatening the safety and efficiency of urban rail transit operation.The basic reason of congestion and its propagation is the insufficiency of transportation supply relative to travel demand.To reduce the security risks caused by passenger congestion and its propagation,under the condition that the transportation supply has nearly reached the ceiling,taking the inflow control measures is of practical significance.Given that passenger flow is dynamically propagating,it is therefore necessary to understand the congestion propagation law on the transit network,including its beginning,propagation and dissipation,on the basis of which the inflow control strategy can be formulated.Focusing on the problem of passenger flow propagation,the main work of the thesis is as follows:(1)The problem of passenger flow propagation is analyzed,including its definition,classification,life cycle,influence,cause of formation and typical peak-hour scenarios.(2)A flow propagation model for urban rail transit line based on CA is built up.Leaving out the passenger transfer process,the flow propagation model is established in the CA framework.An example of Beijing Subway Line 1 is made,showing that using the model,the dynamic process of passenger flow on a transit line can be presented,which is the basis to identify the congestion peaks on the time-space dimension,thus to provide decision support for the inflow control policy.(3)An event-driven simulation model of passenger flow propagation on urban rail transit network is established.The modeling framework is firstly put forward.Four types of diversion ratios are introduced to describe the relations between the flow-in and the flow-out on lines.After calculation of the route choices ratios and the diversion ratios,following the train schedule,the flow states are updated,and finally the time-varying train loads are obtained.An example of Beijing Subway partial network is made,showing the efficiency of the model,which can present the evolution of network congestion and thus gives guidance for the control strategy making.Compared with the microscopic simulation,the model using ODs as the basic simulation unit has higher computing efficiency.(4)Focusing on ordinary peak hours,a method based on passenger flow propagation calculation tool to make inflow control strategy is put forward:firstly,use the propagation tool to identify the potential stations as well as the time period to implement inflow control;secondly,target at the safety as the first goal while the minimization of passenger delays as the second goal;finally,calculate the control intensity using the adapted algorithms.To get the numerical results of a control policy:when using the CA line model as the propagation tool,a backward-pass method is proposed;when using the event-driven network model,a modified PSO algorithm is put forward.Examples show that the proposed methods are able to provide with quantitation basis containing the stations and the intervals to take control as well as the control intensities,which can further improve the congestion situation and enhance the operational safety level.