Urban rail transit(URT) has been playing an important role in urban sustainable development with its advantages of high speed,large capacity,high efficiency and low pollution.Estimating URT network scale is the key to...Urban rail transit(URT) has been playing an important role in urban sustainable development with its advantages of high speed,large capacity,high efficiency and low pollution.Estimating URT network scale is the key to ensure the scientificity and feasibility of its construction.The existing studies on rational scale of URT network have not dealt with the interaction of supply and demand.This paper describes the establishment of a system dynamics model of rational URT network scale determination,considering the interaction between URT construction and city social economic development as well as the dynamic equilibrium of capital supply and traffic demand,and the verification of the model validity by applying it to the case of Wuhan City's URT construction.展开更多
Changchun Railway Vehicle Co.,Ltd.(CRC) was founded in March 2002.Initiated by China's North Locomotive & Rolling Stock Industry (group) Corporation,and based on the main business as well as the capital of the...Changchun Railway Vehicle Co.,Ltd.(CRC) was founded in March 2002.Initiated by China's North Locomotive & Rolling Stock Industry (group) Corporation,and based on the main business as well as the capital of the former Changchun Car Company,CRC was founded as new joint-stock company,展开更多
Passenger flow is the foundation for urban rail transit(URT)operations.However,its cal-culated results from assignment models may deviate from the actual situation in both spa-tial and temporal dimensions,which arouse...Passenger flow is the foundation for urban rail transit(URT)operations.However,its cal-culated results from assignment models may deviate from the actual situation in both spa-tial and temporal dimensions,which arouses more attention and needs to be evaluated in particular.On the other hand,onboard video data from URT trains provides a potential way for model evaluation.This study defines the evaluation problem,and proposes a method-ological solution for evaluating rail transit assignment models in the temporal dimension,which includes qualitative validation and difference quantification.A suitable time granu-larity is determined for the best effectiveness,and onboard video data are used for actual passenger flow extraction.The gap between the actual and calculated data by the model is identified with nonparametric statistical techniques(NPSTs)and quantified with time ser-ies similarity measurement(TSSM)methods.A case study on the Shanghai metro demon-strates the performance of the proposed approach,and several practice implications for URT operation agencies are discussed.展开更多
At certain urban rail transit(URT)stations,large events,emergencies,or holidays often cause a rapid surge in passenger flow,referred to as large passenger flow(LPF)events.The passenger congestion will spread quickly v...At certain urban rail transit(URT)stations,large events,emergencies,or holidays often cause a rapid surge in passenger flow,referred to as large passenger flow(LPF)events.The passenger congestion will spread quickly via transfer stations and affect other stations and lines in the URT network.This study develops a timetable rescheduling and coordinating method for the URT network under LPF events.Firstly,a collaborative adjustment model of train timetables with a backup-vehicle strategy is formulated to simultaneously consider rescheduling and coordinating problems,to reduce the congestion influence for a URT network.Then,a rolling horizon approach is developed to divide the whole adjustment problem into several decision-making stages to ensure solution efficiency.In each decision-making stage,the influence of LPF propagation within the URT network is firstly evaluated.Based on the congestion evaluation results,the proposed method determines whether it is necessary to adjust timetables of the LPF line or other lines.The proposed method is applied to the Xi’an Metro network in China.The results indicate that the proposed method can effectively evaluate and adjust the train timetables for large URT networks under LPF events.展开更多
基金Funded by Independent Innovation Grant of Huazhong University of Science & Technology (No. M2009013)
文摘Urban rail transit(URT) has been playing an important role in urban sustainable development with its advantages of high speed,large capacity,high efficiency and low pollution.Estimating URT network scale is the key to ensure the scientificity and feasibility of its construction.The existing studies on rational scale of URT network have not dealt with the interaction of supply and demand.This paper describes the establishment of a system dynamics model of rational URT network scale determination,considering the interaction between URT construction and city social economic development as well as the dynamic equilibrium of capital supply and traffic demand,and the verification of the model validity by applying it to the case of Wuhan City's URT construction.
文摘Changchun Railway Vehicle Co.,Ltd.(CRC) was founded in March 2002.Initiated by China's North Locomotive & Rolling Stock Industry (group) Corporation,and based on the main business as well as the capital of the former Changchun Car Company,CRC was founded as new joint-stock company,
基金supported by the National Natural Science Foundation of China(Nos.72071147 and 71701152)the Fundamental Research Funds for the Central Universities of China(No.22120220628).
文摘Passenger flow is the foundation for urban rail transit(URT)operations.However,its cal-culated results from assignment models may deviate from the actual situation in both spa-tial and temporal dimensions,which arouses more attention and needs to be evaluated in particular.On the other hand,onboard video data from URT trains provides a potential way for model evaluation.This study defines the evaluation problem,and proposes a method-ological solution for evaluating rail transit assignment models in the temporal dimension,which includes qualitative validation and difference quantification.A suitable time granu-larity is determined for the best effectiveness,and onboard video data are used for actual passenger flow extraction.The gap between the actual and calculated data by the model is identified with nonparametric statistical techniques(NPSTs)and quantified with time ser-ies similarity measurement(TSSM)methods.A case study on the Shanghai metro demon-strates the performance of the proposed approach,and several practice implications for URT operation agencies are discussed.
基金supported by the National Natural Science Foundation of China(No.U2368216 and 72101184)the Shanghai Science and Technology Program(No.21JC1400600)+2 种基金the Natural Science Foundation of Shanghai(No.23ZR1467400)China Postdoctoral Science Foundation(No.2023M732645)the Shanghai Post-Doctoral Excellence Program(No.2022570).
文摘At certain urban rail transit(URT)stations,large events,emergencies,or holidays often cause a rapid surge in passenger flow,referred to as large passenger flow(LPF)events.The passenger congestion will spread quickly via transfer stations and affect other stations and lines in the URT network.This study develops a timetable rescheduling and coordinating method for the URT network under LPF events.Firstly,a collaborative adjustment model of train timetables with a backup-vehicle strategy is formulated to simultaneously consider rescheduling and coordinating problems,to reduce the congestion influence for a URT network.Then,a rolling horizon approach is developed to divide the whole adjustment problem into several decision-making stages to ensure solution efficiency.In each decision-making stage,the influence of LPF propagation within the URT network is firstly evaluated.Based on the congestion evaluation results,the proposed method determines whether it is necessary to adjust timetables of the LPF line or other lines.The proposed method is applied to the Xi’an Metro network in China.The results indicate that the proposed method can effectively evaluate and adjust the train timetables for large URT networks under LPF events.
