| In recent years,with the rapid development of urbanization in China,the number of city resident is increasing synchronously,and their travel demands are becoming more and more diversified.As a critical part of the public transportation system,urban rail transit system optimizes city structure,supports society development,and boosts economic growth.However,the ever-increasing demands from the passengers have brought great challenges to daily passenger transportation.Meanwhile,the construction speed of urban rail transit network is accelerating,the scale of construction is expanding,and the complexity of urban rail transit network is increasing,which lead to problems like coexistence of new-old rail lines,cost rises of the equipment maintenance,and the pressure increases of network maintenance.These problems constantly threaten the smooth operation of the urban rail transit system as well as passengers' safety.Under the doubled pressure caused by the massive travel demand and the much complicated network structure,the frequency of all kinds of emergencies in urban rail transit network is increasing significantly,and the impact caused by the emergencies is becoming much severe.The congestion in urban rail transit network is closely related to passengers' travel choice behavior under this particular scenario.Therefore,analyzing passengers' travel behavior in the urban rail transit network under emergencies and grasping the distribution state of passenger flow in the network,can provide sufficient theoretical basis for the operation and management department of urban rail transit to formulate passenger flow control measures.In this research,domestic and foreign literatures are sorted out and analyzed from the aspects of urban rail transit emergencies,passengers' travel choice behavior,and the propagation of congested passenger flow,etc.,and the positive progress and the problems that need to be improved urgently of the existing research results are summarized.Based on the analysis,the passenger flow data of Guangzhou Metro are used to analyze the distribution characteristics from two aspects as spatial and time.With the stated preference(SP)survey data,passengers' travel choice model under metro emergencies is developed using random regret minimization(RRM)theory and random utility maximization(RUM)theory.Then,based on graph cellular automata and multi-agent based modeling method,together with the analysis of passengers' travel behaviors,the congestion propagation rate is quantified according to different urban rail transit stations.The main content and results are listed as follows:(1)Analyzing of passenger flow distribution characteristics and the influencing factors of passengers' travel choice behavior in the urban rail transit network under emergencies.By comparing the passenger flow data before and after the emergency,it is found that the he emergencies' spatial impact on the passenger flow distribution is mainly reflected on 3 levels: station,line and network.Emergencies' time influence on passenger flow distribution is mainly reflected in the two aspects: travel period(peak and non-peak)and duration of the delay.Through the SP survey of metro passengers,the data of passengers' travel choice behavior under emergencies are obtained,and the survey data are preliminarily analyzed from the perspective of passengers' personal attributes,travel attributes and choice preferences.Through the analysis of 10128 valid samples,it is found that the personal attributes and travel attributes of the metro passengers,such as gender,age,monthly income,travel time,travel purpose,weekly travel times,maximum transfer times and maximum waiting time,will have a significant impact on their travel choice behavior under urban rail transit emergencies.(2)Establishing passengers' travel choice model under urban rail transit emergencies.By introducing the RRM theory and comparing the calibration results of the travel choice model,it is found that the RRM model with semi-compensation characteristics and compromise effect can better describe passengers' travel choice behavior under urban rail transit emergencies.Metro passengers' travel choice model is built based on the comparison,and the results indicate that passengers' acceptance of multiple transfers is significantly improved,and they are no longer excluded from choosing detour routes under the emergencies.In addition,the NL-RRM model is established by combining RRM and RUM,as well as integrating passengers' personal attributes,travel preference and other influencing factors.The calibration results show that this model has a better fitting effect and has a potential advantage in describing passengers' travel choice behaviors under emergencies,which also indicates that the combination of multiple decision rules can better describe the passengers' choice behavior under urban rail transit emergencies.(3)Simulating the propagation process of congested passenger flow under urban rail transit emergencies.The theory of graph cellular automata and the multi-agent modeling technology is used to construct the simulation environment of congested passenger flow propagation in urban rail transit network under emergency.Based on the improved SEIR model,the ASEIR model is proposed as the evolution rule for the state of the graph cellular automata.The simulation results for the entire Guangzhou metro network show that the emergencies in peak periods will lead to longer congestion time and more crowded stations.In addition,the congested passenger flow will also cause the phenomenon of secondary transmission in the urban rail transit network after the emergencies end.However,the propagation time and influence range of congested passenger flow caused by emergencies in nonpeak hours are both smaller than that in peak hours,and there is no such thing as secondary propagation of the congested passenger flow during nonpeak period.(4)Quantifying the congestion propagation rate based on passengers' travel behavior under emergencies.Considering the differences of transfer stations and the non-transfer stations in propagating congestion in the network,together with passengers' travel choice behaviors under urban rail transit emergencies,the congestion propagation rate of each station is quantified,in order to more accurately simulate the congestion propagation process under the emergencies.By modifying the congestion propagation rate and dissipation rate,the influence of relevant passenger flow regulation measures on the network propagation of congested passenger flow under emergencies is studied,and different passenger limiting intensity is included in the simulation study.The results show that when the limiting rate reaches 0.6 during peak hours,the duration of congestion in transfer stations will reduce 50%.While during nonpeak hours,the limiting rate reaches 0.8 can receive significant congestion dissipate effects as well.Moreover,increasing the congestion dissipation rate can also greatly improve the efficiency of handling the congestions in the urban rail transit network under emergencies,and effectively reduce the propagation range and the duration of congested passenger flows in the entire urban rail transit network. |
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