Metro passenger flow control problem is studied under given total inbound demand in this work,which considers passenger demand control and train capacity supply.Relevant connotations are analyzed and a mathematical mo...Metro passenger flow control problem is studied under given total inbound demand in this work,which considers passenger demand control and train capacity supply.Relevant connotations are analyzed and a mathematical model is developed.The decision variables are boarding limiting and stop-skipping strategies and the objective is the maximal passenger profit.And a passenger original station choice model based on utility theory is built to modify the inbound passenger distribution among stations.Algorithm of metro passenger flow control scheme is designed,where two key technologies of stopping-station choice and headway adjustment are given and boarding limiting and train stopping-station scheme are optimized.Finally,a real case of Beijing metro is taken for example to verify validity.The results show that in the three scenarios with different ratios of normal trains to stop-skipping trains,the total limited passenger volume is the smallest and the systematic profit is the largest in scenario 3.展开更多
Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recu...Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processesand the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transferstation streamlines.Design/methodology/approach – The synthesis of stochastic process theory with streamline analysisengenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passengerflow data procured from monitoring systems within the transfer station, a gradient descent optimizationtechnique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorizedpassenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm isimplemented to allocate the intra-station categorized passenger flows across various streamlines, ascertainingthe traffic volume for each.Findings – Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation softwareis engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposedpassenger flow estimation model. The derived solutions are instrumental in formulating a crowd controlstrategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowdmanagement interventions that offer insights for the orchestration of passenger flow and operationalgovernance within metro stations.Originality/value – The construction of an estimation methodology for the real-time streamline traffic flowaugments the model’s dataset, supplanting estimated values derived from surveys or historical datasets withreal-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow managementwithin metro stations.展开更多
基金Projects(RCS2015ZZ002,RCS2014ZT25)supported by State Key Laboratory of Rail Traffic Control&Safety,ChinaProject(2015RC058)supported by Beijing Jiaotong University,China
文摘Metro passenger flow control problem is studied under given total inbound demand in this work,which considers passenger demand control and train capacity supply.Relevant connotations are analyzed and a mathematical model is developed.The decision variables are boarding limiting and stop-skipping strategies and the objective is the maximal passenger profit.And a passenger original station choice model based on utility theory is built to modify the inbound passenger distribution among stations.Algorithm of metro passenger flow control scheme is designed,where two key technologies of stopping-station choice and headway adjustment are given and boarding limiting and train stopping-station scheme are optimized.Finally,a real case of Beijing metro is taken for example to verify validity.The results show that in the three scenarios with different ratios of normal trains to stop-skipping trains,the total limited passenger volume is the smallest and the systematic profit is the largest in scenario 3.
文摘Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processesand the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transferstation streamlines.Design/methodology/approach – The synthesis of stochastic process theory with streamline analysisengenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passengerflow data procured from monitoring systems within the transfer station, a gradient descent optimizationtechnique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorizedpassenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm isimplemented to allocate the intra-station categorized passenger flows across various streamlines, ascertainingthe traffic volume for each.Findings – Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation softwareis engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposedpassenger flow estimation model. The derived solutions are instrumental in formulating a crowd controlstrategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowdmanagement interventions that offer insights for the orchestration of passenger flow and operationalgovernance within metro stations.Originality/value – The construction of an estimation methodology for the real-time streamline traffic flowaugments the model’s dataset, supplanting estimated values derived from surveys or historical datasets withreal-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow managementwithin metro stations.
