Research On Identification And Control Method Of Large Passenger Flow In Urban Rail Transit Station

The construction and operation of urban rail transit in my country have entered a period of large-scale and networked operation.However,with the continuous expansion of the scale of the rail transit network,coupled with system failures,large-scale events,and unreasonable station design capabilities,the passenger flow of stations and lines has increased sharply.At the same time,the contradiction between passenger flow demand and capacity has become increasingly prominent.It is easy to trigger safety risks such as trampling,panic,suffocation,and falling of passengers.In recent years,the impact of the large passenger flow of rail transit has caused many accidents.The risks such as train delays,passenger detention,and crowd trampling caused by large passenger flow are threatening the safe operation of rail transit.The improvement of the service quality of urban rail transit,especially the solution of the problem of large passenger flow in stations,has become a common problem facing the world and urgently needed to be solved.Therefore,how to accurately identify the large passenger flow of rail transit stations and then take control measures in time has become an urgent operational safety problem in urban rail transit under the networked operation condition.This paper takes the rail transit station as the research object;the mechanism of the safety risk triggered by the large passenger flow in the station is researched;the real-time calculation model of the maximum service capacity of the station is designed;the large passenger flow identification and evaluation index system is constructed;the quantitative evaluation method for the identification of the large passenger flow in the station is proposed;the identification and early warning technology of the large passenger flow in the station is studied;the multi-station upward and downward direction coordinated dynamic control technology is studied;Finally,the typical stations and route were selected for case analysis.The main work of the thesis includes the following aspects:(1)Research on the mechanism of safety risk triggered by large passenger flow in urban rail transit stations.Combining the morning and evening peak passenger flow data of Nanjing Metro,the characteristic law(continuity,time and direction regularity,imbalance)of the large passenger flow at the station is studied by the analysis of the occupancy of passenger flow entering/exiting the station during peak hours and the section passenger flow imbalance coefficient.The facilities of rail transit stations are analyzed and the key nodes of passenger flow are determined.Combining the characteristics of large passenger flow and key nodes,the large passenger flow movement characteristic models of the passage,ascending stairs,and descending stairs in the station are constructed respectively based on actual measurement data.These models lay the foundation for the identification of large passenger flow and the research on the mechanism of triggering safety risks.The mechanism of the safety risk triggered by the large passenger flow in the station is analyzed,and a five-step safety risk analysis method is proposed.Finally,taking the Liuzhoudonglu Station and Zhujianglu Station of Nanjing Metro as examples,the safety risk analysis is carried out on the inbound flow line from the inbound AFC gate to the platform in the direction of Mozhoudonglu at Liuzhoudonglu Station and the outbound flow line from the platform to the outbound AFC gate in Zhujianglu Station.The risk analysis results are obtained,which verifies the effectiveness of the model and method.(2)Research on the maximum service capacity of urban rail transit stations.The passenger gathering and dispersal process in rail transit stations are analyzed,and the definition of the maximum service capacity of the station is put forward.Combined with the analysis of the factors affecting the maximum service capacity of the station,based on the real-time Automatic Fare Collection(AFC)data and the walking time of each facility and equipment,a real-time calculation model of the maximum service capacity of the station with a time interval of 5minutes is constructed.This model proposed overcomes the limitation of calculating the maximum service capacity of stations in isolation,static state and large time granularity.The real-time and dynamic calculation of the maximum service capacity of the station is realized,as well as the preliminary identification and early warning of the large passenger flow of the station.It provides theoretical support for the identification and control of large passenger flow.Finally,taking the Zhujianglu Station of Nanjing Metro Line 1 as an example,two comparisons are made:(1)the capacity of rail transit station is compared with the maximum service capacity to obtain the sample data of large passenger flow;(2)the sample data of large passenger flow is compared with actual large passenger flow events to test the consistency of identification results of large passenger flow.Through the above comparison,it strongly proves the efficiency of the constructed maximum service capacity calculation model in large passenger flow identification and early warning.(3)Research on identification method of large passenger flow in urban rail transit station.The inbound,outbound and transfer passenger flow streamlines in the pay area of the station are analyzed.The influencing factors of the passenger flow operating state are studied from four aspects: passenger flow,facilities and equipment,environment and management.Combining the Highway Capacity Manual(HCM2000)and the Transit Capacity and Quality of Service Manual(TCQSM)service level classification standards,the passenger flow operating state in the station is divided to determine the passenger flow state level of the large passenger flow.A large passenger flow identification and evaluation index system that can be specific to a certain facility and equipment is constructed.The threshold interval of different passenger flow state of each rating index is calculated.The weight of each evaluation index is determined by the analytic hierarchy process.A quantitative evaluation method based on the improved matter-element extension model to identify the status of large passenger flow in the station is proposed.The identification and early warning technology of large passenger flow in the station has taken shape.It overcomes the shortcomings of existing large passenger flow identification methods,such as one-sided consideration of evaluation indicators,one evaluation indicator corresponding to only one type of facility and equipment,and the limitations of traditional correlation coefficient calculation models.Finally,a calculation example is analyzed by taking Daxinggong Station of Nanjing Metro as an example.The model analysis result is consistent with the actual result and the judgment result of HCM2000,which proves the effectiveness of the proposed method of large passenger flow identification.(4)Research on multi-station collaborative dynamic control method for large passenger flow of urban rail transit.The coordinated control measures of multiple rail transit stations are studied.The influencing factors of multi-station cooperative dynamic control of large passenger flow are analyzed.The optimization targets are the total detention time of passengers and the sum of early-warning grade coefficients of large passenger flow in each station.The constraints are the limitation of station service capacity,train capacity limitation,the number of people who need to board the train,etc.At the same time,considering the independent control of the transfer passenger flow in the transfer station,the multi-station upward and downward direction coordinated dynamic control model is constructed.The multi-station upward and downward direction coordinated dynamic control technology for large passenger flows has been initially formed.It overcomes the limitations of existing studies that only carry out coordinated control from a single direction and do not consider the overall decline of the warning levels of all stations on the line.Finally,taking Nanjing Metro Line 1 as an example,the warning levels of stations before and after the coordinated control and the full load rate of the intervals before and after the coordinated control are compared and analyzed.At the same time,the average detention rate of the station and the average utilization rate of the interval are selected for analysis.The results show that after the coordinated control,the detention rate and the passenger flow warning level of each station are significantly reduced.The full load rate of each section in the upward and downward directions is also less than 100%.The overall control effect of the line is very good.