First,statistics on the operational lines and mileage of urban rail transit in China are conducted.The results show that,as of Dec.31,2025,there were 60 cities with urban rail transit in operation nationwide,with a to...First,statistics on the operational lines and mileage of urban rail transit in China are conducted.The results show that,as of Dec.31,2025,there were 60 cities with urban rail transit in operation nationwide,with a total operational mileage of approximately 12837.8 km(excluding the electronic guideway rubber-tired system,there were 57 cities,with a total operational mileage of 12651.6 km).The metro system dominates,while low-capacity systems exhibit a multi-modal development pattern.Subsequently,the characteristics of China′s urban rail transit industry development are analyzed,indicating that:(1)It should closely align with the theme of urban intensive development,promote quality improvement and efficiency enhancement of existing lines,and focus on the supporting role of initial passenger flow for new line construction,multi-network integration,and economic and financial sustainability.(2)Significant innovative achievements have been made in safety resilience,green and low-carbon development,intelligent construction,and digital transformation.Finally,development recommendations for the"15th Five-Year Plan"period are proposed:promoting cost reduction and efficiency improvement in the rail transit industry,enhancing the operational efficiency of existing networks,continuously exploring railway services for urban commuting,strengthening external exchanges,and driving the"going global"strategy of the urban rail transit industry.展开更多
This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station...This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station planning and development.Data from 159 metro stations in Nanjing,collected over a 14-d period,were analyzed to identify changes in weekday and weekend ridership patterns.The analysis included explanatory variables grouped into three categories:urban spatial variables,socioeconomic vari-ables,and transit service variables.A geographically and temporally weighted regression(GTWR)model was developed,and its performance was compared with that of ordinary least squares(OLS)and geographically weighted regression(GWR)models.The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment.In addition,the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions,revealing distinct patterns.Notably,the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays.These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.展开更多
As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic fi...As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic field”centered on rail networks,thereby alleviating such temporal-spatial pressures.This paper adopts an integrated temporal-spatial analytical framework.Following a conceptual clarification of the transit economic field,it dissects the mechanisms through which rail transit improves mobility and examines how this field influences urban spatial patterns,temporal dynamics,and their interrelationships.It constructs a theoretical framework to explain the co-development of transit economic fields and cities,supplemented by empirical case studies.The key findings are as follows:Firstly,the transit economic field represents a high-density development model that expands both horizontally and vertically around rail networks.It mitigates temporal-spatial conflicts.Secondly,with rail networks as the core,the field integrates diverse spatial functions,facilitating the establishment of economic connections and stabilizing temporal-spatial relationships.Thirdly,the transit economic field contributes to the preservation of urban natural ecosystems and enhances urban livability.Overall,this research can provide insights for promoting rail transit-oriented development transitions in large cities and urban agglomerations.展开更多
Urban rail transit is an efficient and environmentally friendly mode of transport,which is an important means of transportation for passengers.From a holistic point of view,this paper constructs an urban rail transit ...Urban rail transit is an efficient and environmentally friendly mode of transport,which is an important means of transportation for passengers.From a holistic point of view,this paper constructs an urban rail transit interchange topology(URTIT)network based on the interchange relationships among lines.We investigate a unique influence propagation mechanism to explore the impact of applying new technologies on the passenger travel behavior of urban rail transit.We analyze the influence from three aspects:the influence range,the influence propagation path,and the influence intensity.Based on the Dijkstra algorithm,the influence propagation paths are found according to the shortest transfer time.The improved path-based gravity model is applied to measure the influence intensity.The case study on urban rail transit in Beijing,China is carried out.The influence propagation mechanism of a single line in the Beijing URTIT network is analyzed,considering that Beijing Subway Line S1 is equipped with magnetic levitation technology.We not only quantify the impact of technologies on passenger travel behavior of urban rail transit,but also perform the sensitivity analysis.To avoid randomness,the influence propagation mechanisms of all lines are explored in this paper.The research results correspond to the situation in reality,which can provide certain references for urban rail transit operation and planning.展开更多
Within the transition process of urban rail transit systems,the challenges of high energy consumption,increasing carbon emissions,limited economic viability,and intricate risks emerge as significant hurdles.This paper...Within the transition process of urban rail transit systems,the challenges of high energy consumption,increasing carbon emissions,limited economic viability,and intricate risks emerge as significant hurdles.This paper proposes a novel energy utilization framework for the urban rail transit system that incorporates underground energy storage systems characterized by high resilience and low carbon.First,existing methods employed in urban rail transit are comprehensively reviewed.Then,a novel framework and strategic significance of the urban rail transit system incorporating underground energy storage systems are introduced.This integration effectively utilizes and manages diverse renewable energy sources and the available space resources.The viability is demonstrated through a case study by combining Nanjing metro.Finally,suggestions for research in pivotal areas are summarized.展开更多
The accurate prediction and analysis of emergencies in Urban Rail Transit Systems(URTS)are essential for the development of effective early warning and prevention mechanisms.This study presents an integrated perceptio...The accurate prediction and analysis of emergencies in Urban Rail Transit Systems(URTS)are essential for the development of effective early warning and prevention mechanisms.This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data.To address issues related to data structuredness and missing values,we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network(ER-GAIN)for data structuring and imputation.Additionally,to mitigate the impact of imbalanced data on the predictive performance of emergencies,we introduced an Adaptive Boosting Ensemble Model(AdaBoost)to forecast the key features of emergencies,including event types and levels.We also utilized Information Gain(IG)to analyze and rank the causes of various significant emergencies.Experimental results indicate that,compared to baseline data imputation models,ER-GAIN improved the prediction accuracy of key emergency features by 3.67%and 3.78%,respectively.Furthermore,AdaBoost enhanced the accuracy by over 4.34%and 3.25%compared to baseline predictivemodels.Through causation analysis,we identified the critical causes of train operation and fire incidents.The findings of this research will contribute to the establishment of early warning and prevention mechanisms for emergencies in URTS,potentially leading to safer and more reliable URTS operations.展开更多
To address the challenges of supply-demand imbal-ance in rail transit and the complex passenger flow interactions among multiple hub stations under high-passenger-volume scenarios,this study proposes an optimized rail...To address the challenges of supply-demand imbal-ance in rail transit and the complex passenger flow interactions among multiple hub stations under high-passenger-volume scenarios,this study proposes an optimized rail transit scheduling method based on a flexible train formation strat-egy(FTFS).By constructing interaction parameters that characterize the coupling effects of high passenger flow across multiple hubs,a multiobjective optimization model is developed to minimize passenger waiting time at hub sta-tions and operational costs.An improved nondominated sorting genetic algorithm incorporating chaotic mapping and adaptive evolutionary parameters is designed for efficient so-lution optimization.This method overcomes the limitations of fixed train formations by supporting diversified modular unit detachment and reconnection,enabling dynamic capac-ity adjustment and efficient rolling stock circulation.A case study on Nanjing Metro Line 1 demonstrates that the FTFS reduces the average waiting time at hub stations by 47.2%,alleviates train congestion by approximately 18.6%,and re-duces the operational costs under low-demand scenarios by 44.8%.Pareto frontier analysis further reveals the trade-off mechanism between transport capacity elasticity and opera-tional costs.These findings validate the effectiveness of the flexible train formation model in mitigating platform conges-tion and enhancing passenger flow evacuation efficiency at transport hubs,providing multiobjective decision-making support for managing extreme passenger flow during holi-days and peak events.展开更多
The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach ...The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions.However,the current structured degree of the URT emergency knowledge base remains low,and the domain questions lack labeled datasets,resulting in a large deviation between the consultation outcomes and the intended objectives.To address this issue,this paper proposes a question intention recognition model for the URT emergency domain,leveraging knowledge graph(KG)and data enhancement technology.First,a structured storage of emergency cases and emergency plans is realized based on KG.Subsequently,a comprehensive question template is developed,and the labeled dataset of emergency domain questions in URT is generated through the KG.Lastly,data enhancement is applied by prompt learning and the NLP Chinese Data Augmentation(NLPCDA)tool,and the intention recognition model combining Generalized Auto-regression Pre-training for Language Understanding(XLNet)and Recurrent Convolutional Neural Network for Text Classification(TextRCNN)is constructed.Word embeddings are generated by XLNet,context information is further captured using Bidirectional Long Short-Term Memory Neural Network(BiLSTM),and salient features are extracted with Convolutional Neural Network(CNN).Experimental results demonstrate that the proposed model can enhance the clarity of classification and the identification of domain questions,thereby providing supportive knowledge for emergency decision-making in URT.展开更多
Many railway turnouts are often installed near metro depots and stations,leading to significant environmental vibrations reaching nearby infrastructure.Vibration in turnout zones can originate from various sources,suc...Many railway turnouts are often installed near metro depots and stations,leading to significant environmental vibrations reaching nearby infrastructure.Vibration in turnout zones can originate from various sources,such as rail joints,wheel-load transitions,uneven stiffnesses,rail corrugation,and small-radius curves.These factors contribute to turnout zones having considerably higher vibration levels than plain track sections.Additionally,in urban rapid transit systems,higher train speeds exacerbate wheel–rail impact excitation,further intensifying such vibrations.Despite turnout zones accounting for a large share of environmental vibrations,there have been few systematic studies on their specific sources and mechanisms in the context of rapid transit systems.This knowledge gap has hindered the development and optimization of vibration mitigation strategies for turnout structures.Therefore,in this study,we investigate five representative sets of turnouts from a rapid transit system in a Chinese city,with train speeds ranging from 80 to 150 km/h.Field tests were conducted on real operating trains,with vibration accelerations measured at turnout rails and tunnel walls.This study systematically examines the effects of turnout structure,train carriage position,speed,and vibration mitigation measures on the vibration source characteristics.Time-frequency methods were employed to analyze the test data.Our findings reveal that when train speeds exceed 100 km/h,leading and trailing carriages passing through turnouts induce low-frequency vibrations below 80 Hz,thus generating vibrations in the human-sensitive frequency range.Moreover,train-induced vibrations in turnout zones are primarily concentrated in three frequency bands:0–20 Hz(associated with structural and stiffness irregularities in the turnouts),50–80 Hz(P2 resonance of the wheel–rail system),and 150–200 Hz(natural frequencies of the rails).展开更多
To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved...To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.展开更多
The skip-stop operation strategy （SOS） is rarely applied to Chinese urban rail transit networks because it is a simple scheme and a less universally popular transportation service. However, the SOS has performance a...The skip-stop operation strategy （SOS） is rarely applied to Chinese urban rail transit networks because it is a simple scheme and a less universally popular transportation service. However, the SOS has performance advantages, in that the total trip time can be reduced depending on the number of skipped stations, crowds of passengers can be rapidly evacuated at congested stations in peak periods, and the cost to transit companies is reduced. There is a contradiction between reducing the trip time under the SOS and increasing the passengers＇ waiting times under an all-stop scheme. Given this situation, the three objectives of our study were to minimize the waiting and trip times of all passengers and the travel times of trains. A comprehensive estimation model is presented for the SOS. The mechanism through which the trip time for all passengers is affected by the SOS is analyzed in detail. A 0-I integer programming formulation is established for the three objectives, and is solved using a tabu search algorithm. Finally, an example is presented to demonstrate that the estimation method for the SOS is capable of optimizing the timetable and operation schemes for a Chinese urban rail transit network.展开更多
The train plan of urban rail transit under multi-routing mode can be divided into three parts： train formation, train operation periods and corresponding train counts of each routing in each period. Based on the anal...The train plan of urban rail transit under multi-routing mode can be divided into three parts： train formation, train operation periods and corresponding train counts of each routing in each period. Based on the analysis of passen- ger＇s general travel expenses and operator＇s benefits, the constraints and objective functions are defined and the multiobjective optimization model for the train plan of urban rail transit is presented. Factors considered in the multi- objective optimization model include transport capacity, the requirements of traffic organization, corporation benefits, passenger demands, and passenger choice behavior under multi-train-routing mode. According to the characteristics of this model and practical planning experience, a three-phase solution was designed to gradually optimize the train formarion, train counts as well as operation periods. The instance of Changsha Metro Line 2 validates the feasibility and efficiency of this approach.展开更多
In recent years, there has been rapid growth of Chinese rail transit networks. Many of these networks require elevated bridges. This results in a bridge-borne noise source, which occurs in addition to the main noise s...In recent years, there has been rapid growth of Chinese rail transit networks. Many of these networks require elevated bridges. This results in a bridge-borne noise source, which occurs in addition to the main noise source （i.e., wheel-rail interactions）. Bridge-borne noise is attracting increasing attention because of its low-frequency noise characteristics. This review paper first analyzes the space distribution, spectral characteristics, and sound pressure levels of noise radiated by all-concrete, steel- concrete composite, and all-steel bridges, mainly according to experimental studies. Second, this paper reviews exist- ing theoretical prediction models of noise emanating from bridges： the semianalytical method, the Rayleigh integral method, the boundary element method, and statistical energy analysis. Several case studies are reviewed, and their results are discussed. Finally, according to the results of the current review, the main factors affecting bridgeborne noise are analyzed, several noise reduction measures are proposed for different types of bridges, and their effectiveness is demonstrated.展开更多
A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that th...A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that the time varying original-destination demand and passenger path choice probability were given. Passengers were assumed not to change their destinations and travel paths after delay occurs. CapaciW constraints of train and queue rules of alighting and boarding were taken into account. By using the time-driven simulation, the states of passengers, trains and other facilities in the network were updated every time step. The proposed methodology was also tested in a real network, for demonstration. The results reveal that short train delay does not necessarily result in passenger delays, while, on the contrary, some passengers may get benefits from the short delay. However, large initial train delay may result in not only knock-on train and passenger delays along the same line, but also the passenger delays across the entire rail transit network.展开更多
In order to study the spatiotemporal characteristics of the dockless bike sharing system(BSS)around urban rail transit stations,new normalized calculation methods are proposed to explore the temporal and spatial usage...In order to study the spatiotemporal characteristics of the dockless bike sharing system(BSS)around urban rail transit stations,new normalized calculation methods are proposed to explore the temporal and spatial usage patterns of the dockless BSS around rail transit stations by using 5-weekday dockless bike sharing trip data in Nanjing,China.First,the rail transit station area(RTSA)is defined by extracting shared bike trips with trip ends falling into the area.Then,the temporal and spatial decomposition methods are developed and two criterions are calculated,namely,normalized dynamic variation of bikes(NDVB)and normalized spatial distribution of trips(NSDT).Furthermore,the temporal and spatial usage patterns are clustered and the corresponding geographical distributions of shared bikes are determined.The results show that four temporal usage patterns and two spatial patterns of dockless BSS are finally identified.Area type(urban center and suburb)has a great influence on temporal usage patterns.Spatial usage patterns are irregular and affected by limited directions,adjacent rail transit stations and street networks.The findings can help form a better understanding of dockless shared bike users behavior around rail transit stations,which will contribute to improving the service and efficiency of both rail transit and BSS.展开更多
Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,incl...Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,including real-time availability,sparsity,and high-dimensionality issues,and the impact of the pandemic.Consequently,this study proposes a unified framework called the physics-guided adaptive graph spatial–temporal attention network(PAG-STAN)for metro OD demand prediction under pandemic conditions.Specifically,PAG-STAN introduces a real-time OD estimation module to estimate real-time complete OD demand matrices.Subsequently,a novel dynamic OD demand matrix compression module is proposed to generate dense real-time OD demand matrices.Thereafter,PAG-STAN leverages various heterogeneous data to learn the evolutionary trend of future OD ridership during the pandemic.Finally,a masked physics-guided loss function(MPG-loss function)incorporates the physical quantity information between the OD demand and inbound flow into the loss function to enhance model interpretability.PAG-STAN demonstrated favorable performance on two real-world metro OD demand datasets under the pandemic and conventional scenarios,highlighting its robustness and sensitivity for metro OD demand prediction.A series of ablation studies were conducted to verify the indispensability of each module in PAG-STAN.展开更多
文摘First,statistics on the operational lines and mileage of urban rail transit in China are conducted.The results show that,as of Dec.31,2025,there were 60 cities with urban rail transit in operation nationwide,with a total operational mileage of approximately 12837.8 km(excluding the electronic guideway rubber-tired system,there were 57 cities,with a total operational mileage of 12651.6 km).The metro system dominates,while low-capacity systems exhibit a multi-modal development pattern.Subsequently,the characteristics of China′s urban rail transit industry development are analyzed,indicating that:(1)It should closely align with the theme of urban intensive development,promote quality improvement and efficiency enhancement of existing lines,and focus on the supporting role of initial passenger flow for new line construction,multi-network integration,and economic and financial sustainability.(2)Significant innovative achievements have been made in safety resilience,green and low-carbon development,intelligent construction,and digital transformation.Finally,development recommendations for the"15th Five-Year Plan"period are proposed:promoting cost reduction and efficiency improvement in the rail transit industry,enhancing the operational efficiency of existing networks,continuously exploring railway services for urban commuting,strengthening external exchanges,and driving the"going global"strategy of the urban rail transit industry.
基金The National Key Research and Development Program of China(No.2022YFC3800201).
文摘This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station planning and development.Data from 159 metro stations in Nanjing,collected over a 14-d period,were analyzed to identify changes in weekday and weekend ridership patterns.The analysis included explanatory variables grouped into three categories:urban spatial variables,socioeconomic vari-ables,and transit service variables.A geographically and temporally weighted regression(GTWR)model was developed,and its performance was compared with that of ordinary least squares(OLS)and geographically weighted regression(GWR)models.The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment.In addition,the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions,revealing distinct patterns.Notably,the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays.These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.
基金Hubei Social Science Foundation Project“Research on the Relationship Between Rail Transit and Intensive and Sustainable Development of Large Cities”(2020052)。
文摘As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic field”centered on rail networks,thereby alleviating such temporal-spatial pressures.This paper adopts an integrated temporal-spatial analytical framework.Following a conceptual clarification of the transit economic field,it dissects the mechanisms through which rail transit improves mobility and examines how this field influences urban spatial patterns,temporal dynamics,and their interrelationships.It constructs a theoretical framework to explain the co-development of transit economic fields and cities,supplemented by empirical case studies.The key findings are as follows:Firstly,the transit economic field represents a high-density development model that expands both horizontally and vertically around rail networks.It mitigates temporal-spatial conflicts.Secondly,with rail networks as the core,the field integrates diverse spatial functions,facilitating the establishment of economic connections and stabilizing temporal-spatial relationships.Thirdly,the transit economic field contributes to the preservation of urban natural ecosystems and enhances urban livability.Overall,this research can provide insights for promoting rail transit-oriented development transitions in large cities and urban agglomerations.
基金supported by the Beijing Natural Science Foundation(Grant No.L231009)National Natural Science Foundation of China(Grant No.72288101)Fundamental Research Funds for the Central Universities(Grant No.2022JBZY017)。
文摘Urban rail transit is an efficient and environmentally friendly mode of transport,which is an important means of transportation for passengers.From a holistic point of view,this paper constructs an urban rail transit interchange topology(URTIT)network based on the interchange relationships among lines.We investigate a unique influence propagation mechanism to explore the impact of applying new technologies on the passenger travel behavior of urban rail transit.We analyze the influence from three aspects:the influence range,the influence propagation path,and the influence intensity.Based on the Dijkstra algorithm,the influence propagation paths are found according to the shortest transfer time.The improved path-based gravity model is applied to measure the influence intensity.The case study on urban rail transit in Beijing,China is carried out.The influence propagation mechanism of a single line in the Beijing URTIT network is analyzed,considering that Beijing Subway Line S1 is equipped with magnetic levitation technology.We not only quantify the impact of technologies on passenger travel behavior of urban rail transit,but also perform the sensitivity analysis.To avoid randomness,the influence propagation mechanisms of all lines are explored in this paper.The research results correspond to the situation in reality,which can provide certain references for urban rail transit operation and planning.
基金supported by the National Natural Science Foundation of China(Grant numbers 52177112 and 52278419)the Chinese Academy of Engineering(Grant number 2022--XY-75).
文摘Within the transition process of urban rail transit systems,the challenges of high energy consumption,increasing carbon emissions,limited economic viability,and intricate risks emerge as significant hurdles.This paper proposes a novel energy utilization framework for the urban rail transit system that incorporates underground energy storage systems characterized by high resilience and low carbon.First,existing methods employed in urban rail transit are comprehensively reviewed.Then,a novel framework and strategic significance of the urban rail transit system incorporating underground energy storage systems are introduced.This integration effectively utilizes and manages diverse renewable energy sources and the available space resources.The viability is demonstrated through a case study by combining Nanjing metro.Finally,suggestions for research in pivotal areas are summarized.
基金supported by the Fundamental Research Funds for the Central Universities(grant number 2024YJS096)National Natural Science Foundation of China(grant numbers 62433005,62272036,62173167).
文摘The accurate prediction and analysis of emergencies in Urban Rail Transit Systems(URTS)are essential for the development of effective early warning and prevention mechanisms.This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data.To address issues related to data structuredness and missing values,we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network(ER-GAIN)for data structuring and imputation.Additionally,to mitigate the impact of imbalanced data on the predictive performance of emergencies,we introduced an Adaptive Boosting Ensemble Model(AdaBoost)to forecast the key features of emergencies,including event types and levels.We also utilized Information Gain(IG)to analyze and rank the causes of various significant emergencies.Experimental results indicate that,compared to baseline data imputation models,ER-GAIN improved the prediction accuracy of key emergency features by 3.67%and 3.78%,respectively.Furthermore,AdaBoost enhanced the accuracy by over 4.34%and 3.25%compared to baseline predictivemodels.Through causation analysis,we identified the critical causes of train operation and fire incidents.The findings of this research will contribute to the establishment of early warning and prevention mechanisms for emergencies in URTS,potentially leading to safer and more reliable URTS operations.
基金Key Project of the National Natural Science Foundation of China (No. 52432011)the National Natural Science Foundation of China (No. 524B2153)。
文摘To address the challenges of supply-demand imbal-ance in rail transit and the complex passenger flow interactions among multiple hub stations under high-passenger-volume scenarios,this study proposes an optimized rail transit scheduling method based on a flexible train formation strat-egy(FTFS).By constructing interaction parameters that characterize the coupling effects of high passenger flow across multiple hubs,a multiobjective optimization model is developed to minimize passenger waiting time at hub sta-tions and operational costs.An improved nondominated sorting genetic algorithm incorporating chaotic mapping and adaptive evolutionary parameters is designed for efficient so-lution optimization.This method overcomes the limitations of fixed train formations by supporting diversified modular unit detachment and reconnection,enabling dynamic capac-ity adjustment and efficient rolling stock circulation.A case study on Nanjing Metro Line 1 demonstrates that the FTFS reduces the average waiting time at hub stations by 47.2%,alleviates train congestion by approximately 18.6%,and re-duces the operational costs under low-demand scenarios by 44.8%.Pareto frontier analysis further reveals the trade-off mechanism between transport capacity elasticity and opera-tional costs.These findings validate the effectiveness of the flexible train formation model in mitigating platform conges-tion and enhancing passenger flow evacuation efficiency at transport hubs,providing multiobjective decision-making support for managing extreme passenger flow during holi-days and peak events.
基金supported in part by the National Natural Science Foundation of China.The funding numbers 62433005,62272036,62132003,and 62173167.
文摘The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions.However,the current structured degree of the URT emergency knowledge base remains low,and the domain questions lack labeled datasets,resulting in a large deviation between the consultation outcomes and the intended objectives.To address this issue,this paper proposes a question intention recognition model for the URT emergency domain,leveraging knowledge graph(KG)and data enhancement technology.First,a structured storage of emergency cases and emergency plans is realized based on KG.Subsequently,a comprehensive question template is developed,and the labeled dataset of emergency domain questions in URT is generated through the KG.Lastly,data enhancement is applied by prompt learning and the NLP Chinese Data Augmentation(NLPCDA)tool,and the intention recognition model combining Generalized Auto-regression Pre-training for Language Understanding(XLNet)and Recurrent Convolutional Neural Network for Text Classification(TextRCNN)is constructed.Word embeddings are generated by XLNet,context information is further captured using Bidirectional Long Short-Term Memory Neural Network(BiLSTM),and salient features are extracted with Convolutional Neural Network(CNN).Experimental results demonstrate that the proposed model can enhance the clarity of classification and the identification of domain questions,thereby providing supportive knowledge for emergency decision-making in URT.
基金supported by the National Natural Science Foundation of China(Nos.U2568212,52388102,52478474,and 52472458)the Sichuan Science and Technology Program(Nos.2025NSFTD0013,2024NSFSC0003,and 2025YFHZ0035)the National Key R&D Program of China(Nos.2023YFB2604304,2023YFB2604302,and 2023YFB2604303).
文摘Many railway turnouts are often installed near metro depots and stations,leading to significant environmental vibrations reaching nearby infrastructure.Vibration in turnout zones can originate from various sources,such as rail joints,wheel-load transitions,uneven stiffnesses,rail corrugation,and small-radius curves.These factors contribute to turnout zones having considerably higher vibration levels than plain track sections.Additionally,in urban rapid transit systems,higher train speeds exacerbate wheel–rail impact excitation,further intensifying such vibrations.Despite turnout zones accounting for a large share of environmental vibrations,there have been few systematic studies on their specific sources and mechanisms in the context of rapid transit systems.This knowledge gap has hindered the development and optimization of vibration mitigation strategies for turnout structures.Therefore,in this study,we investigate five representative sets of turnouts from a rapid transit system in a Chinese city,with train speeds ranging from 80 to 150 km/h.Field tests were conducted on real operating trains,with vibration accelerations measured at turnout rails and tunnel walls.This study systematically examines the effects of turnout structure,train carriage position,speed,and vibration mitigation measures on the vibration source characteristics.Time-frequency methods were employed to analyze the test data.Our findings reveal that when train speeds exceed 100 km/h,leading and trailing carriages passing through turnouts induce low-frequency vibrations below 80 Hz,thus generating vibrations in the human-sensitive frequency range.Moreover,train-induced vibrations in turnout zones are primarily concentrated in three frequency bands:0–20 Hz(associated with structural and stiffness irregularities in the turnouts),50–80 Hz(P2 resonance of the wheel–rail system),and 150–200 Hz(natural frequencies of the rails).
基金by National Natural Science Foundation of China(62373142,62033014)Natural Science Foundation of Hunan Province(2025JJ70017,2022JJ50074).
文摘To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.
基金financed by the National Basic Research Program of China, under project ID 2012CB725403
文摘The skip-stop operation strategy （SOS） is rarely applied to Chinese urban rail transit networks because it is a simple scheme and a less universally popular transportation service. However, the SOS has performance advantages, in that the total trip time can be reduced depending on the number of skipped stations, crowds of passengers can be rapidly evacuated at congested stations in peak periods, and the cost to transit companies is reduced. There is a contradiction between reducing the trip time under the SOS and increasing the passengers＇ waiting times under an all-stop scheme. Given this situation, the three objectives of our study were to minimize the waiting and trip times of all passengers and the travel times of trains. A comprehensive estimation model is presented for the SOS. The mechanism through which the trip time for all passengers is affected by the SOS is analyzed in detail. A 0-I integer programming formulation is established for the three objectives, and is solved using a tabu search algorithm. Finally, an example is presented to demonstrate that the estimation method for the SOS is capable of optimizing the timetable and operation schemes for a Chinese urban rail transit network.
基金supported by the National Natural Science Foundation of China (No. 70901076)Research Fund for the Doctoral Program of Higher Education of China (No. 20090162120021)Natural Science Foundation of Hunan Province (No. 10JJ4046)
文摘The train plan of urban rail transit under multi-routing mode can be divided into three parts： train formation, train operation periods and corresponding train counts of each routing in each period. Based on the analysis of passen- ger＇s general travel expenses and operator＇s benefits, the constraints and objective functions are defined and the multiobjective optimization model for the train plan of urban rail transit is presented. Factors considered in the multi- objective optimization model include transport capacity, the requirements of traffic organization, corporation benefits, passenger demands, and passenger choice behavior under multi-train-routing mode. According to the characteristics of this model and practical planning experience, a three-phase solution was designed to gradually optimize the train formarion, train counts as well as operation periods. The instance of Changsha Metro Line 2 validates the feasibility and efficiency of this approach.
基金financial support from the National Natural Science Foundation of China(Grant Nos.51308469 and 51378429)the International Cooperation Program of Sichuan Province(Grant No.2016HH0076)
文摘In recent years, there has been rapid growth of Chinese rail transit networks. Many of these networks require elevated bridges. This results in a bridge-borne noise source, which occurs in addition to the main noise source （i.e., wheel-rail interactions）. Bridge-borne noise is attracting increasing attention because of its low-frequency noise characteristics. This review paper first analyzes the space distribution, spectral characteristics, and sound pressure levels of noise radiated by all-concrete, steel- concrete composite, and all-steel bridges, mainly according to experimental studies. Second, this paper reviews exist- ing theoretical prediction models of noise emanating from bridges： the semianalytical method, the Rayleigh integral method, the boundary element method, and statistical energy analysis. Several case studies are reviewed, and their results are discussed. Finally, according to the results of the current review, the main factors affecting bridgeborne noise are analyzed, several noise reduction measures are proposed for different types of bridges, and their effectiveness is demonstrated.
基金Project(51008229)supported by the National Natural Science Foundation of ChinaProject supported by Key Laboratory of Road and Traffic Engineering of Tongji University,China
文摘A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that the time varying original-destination demand and passenger path choice probability were given. Passengers were assumed not to change their destinations and travel paths after delay occurs. CapaciW constraints of train and queue rules of alighting and boarding were taken into account. By using the time-driven simulation, the states of passengers, trains and other facilities in the network were updated every time step. The proposed methodology was also tested in a real network, for demonstration. The results reveal that short train delay does not necessarily result in passenger delays, while, on the contrary, some passengers may get benefits from the short delay. However, large initial train delay may result in not only knock-on train and passenger delays along the same line, but also the passenger delays across the entire rail transit network.
基金The National Key R&D Program of China(No.2018YFB1600900)the Project of International Cooperation and Exchange of the National Natural Science Foundation of China(No.51561135003)the Key Project of National Natural Science Foundation of China(No.51338003)
文摘In order to study the spatiotemporal characteristics of the dockless bike sharing system(BSS)around urban rail transit stations,new normalized calculation methods are proposed to explore the temporal and spatial usage patterns of the dockless BSS around rail transit stations by using 5-weekday dockless bike sharing trip data in Nanjing,China.First,the rail transit station area(RTSA)is defined by extracting shared bike trips with trip ends falling into the area.Then,the temporal and spatial decomposition methods are developed and two criterions are calculated,namely,normalized dynamic variation of bikes(NDVB)and normalized spatial distribution of trips(NSDT).Furthermore,the temporal and spatial usage patterns are clustered and the corresponding geographical distributions of shared bikes are determined.The results show that four temporal usage patterns and two spatial patterns of dockless BSS are finally identified.Area type(urban center and suburb)has a great influence on temporal usage patterns.Spatial usage patterns are irregular and affected by limited directions,adjacent rail transit stations and street networks.The findings can help form a better understanding of dockless shared bike users behavior around rail transit stations,which will contribute to improving the service and efficiency of both rail transit and BSS.
基金supported by the National Natural Science Foundation of China(72288101,72201029,and 72322022).
文摘Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,including real-time availability,sparsity,and high-dimensionality issues,and the impact of the pandemic.Consequently,this study proposes a unified framework called the physics-guided adaptive graph spatial–temporal attention network(PAG-STAN)for metro OD demand prediction under pandemic conditions.Specifically,PAG-STAN introduces a real-time OD estimation module to estimate real-time complete OD demand matrices.Subsequently,a novel dynamic OD demand matrix compression module is proposed to generate dense real-time OD demand matrices.Thereafter,PAG-STAN leverages various heterogeneous data to learn the evolutionary trend of future OD ridership during the pandemic.Finally,a masked physics-guided loss function(MPG-loss function)incorporates the physical quantity information between the OD demand and inbound flow into the loss function to enhance model interpretability.PAG-STAN demonstrated favorable performance on two real-world metro OD demand datasets under the pandemic and conventional scenarios,highlighting its robustness and sensitivity for metro OD demand prediction.A series of ablation studies were conducted to verify the indispensability of each module in PAG-STAN.
