This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control...This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control input. The ATSMC structure is designed by considering the nonlinear characteristics of the dynamic model and the parametric uncertainties of the train operation in real time. A nonsingular terminal sliding mode control is employed to make the system quickly reach a stable state within a finite time, which makes the control input less adjust to guarantee the riding comfort. An adaptive mechanism is used to estimate controller parameters to get rid of the need of the prior knowledge about the bounds of system uncertainty. Simulations are presented to demonstrate the effectiveness of the proposed controller, which has robust performance to deal with the external disturbance and system parametric uncertainties. Thereby, the system guarantees the train operation to be accurate and comfortable.展开更多
The determination and optimization of Automatic Train Operation(ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider m...The determination and optimization of Automatic Train Operation(ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider many goals of the train operation, such as safety, accuracy, comfort, energy saving and so on. This paper designs a set of efficient and universal multi-objective control strategy. Firstly, based on the analysis of urban rail transit and its operating environment, the multi-objective optimization model considering all the indexes of train operation is established by using multi-objective optimization theory. Secondly, Non-dominated Sorting Genetic Algorithm II(NSGA-II) is used to solve the model, and the optimal speed curve of train running is generated.Finally, the intelligent controller is designed by the combination of fuzzy controller algorithm and the predictive control algorithm, which can control and optimize the train operation in real time. Then the robustness of the control system can ensure and the requirements for multi-objective in train operation can be satisfied.展开更多
Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of...Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.Design/methodology/approach–The authors optimize the train operational plan in a special network layout,i.e.an urban rail corridor with dead-end terminal yard,by decomposing it into two sub-problems:train timetable optimization and rolling stock circulation optimization.As for train timetable optimization,the authors propose a schedule-based passenger flow assignment method,construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm.For the optimization of rolling stock circulation,the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.Findings–The case study shows that the train operational plan developed by the study’s approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.Originality/value–The example verifies the efficiency of the model and algorithm.展开更多
The research background is based on great consumption of urban rail transit energy, through summarizing the research of scholars at home and abroad, the comprehensive research including train operation pattern, the tr...The research background is based on great consumption of urban rail transit energy, through summarizing the research of scholars at home and abroad, the comprehensive research including train operation pattern, the train traction characteristics and optimization design of integrated research has carried out in this paper, by using OPENTRACK software simulation to verify the optimization results according to different line features finally. The aim of this paper is to explore ways and methods of traction strategy optimization under the condition of trains timing energy saving. The main research contents of this paper are based on the research status at home and abroad, first of all, the different operating modes of the train running on the line are analysed, including the time saving mode, the energy saving mode and timing energy saving mode, and quantitative analysed the influence of different operation modes on vehicle energy consumption. The influence factors and traction calculation method of energy consumption of train running are studied. Firstly, the factors that affect the energy consumption of the train are analysed, including the basic facilities and transport organization mode. On the basis of this, the train load and running status of the train are analysed, and the model of the train movement and energy consumption are calculated. The OPENTRACK software is used to establish the actual circuit model, and the simulation is verified. The results show that the reasonable operation mode of the train operation mode can greatly reduce the energy consumption.展开更多
A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of op...A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme,and the initial population can be formed by the way.The fitness function can be designed by the design requirements of the train control stop error,time error and energy consumption.the effectiveness of new individual can be ensured by checking the validity of the original individual when its in the process of selection,crossover and mutation,and the optimal algorithm will be joined all the operators to make the new group not eliminate on the best individual of the last generation.The simulation result shows that the proposed genetic algorithm comparing with the optimized multi-particle simulation model can reduce more than 10%energy consumption,it can provide a large amount of sub-optimal solution and has obvious optimization effect.展开更多
As a long-term strategic policy of Chinas social and economic development, energy conservation is also an important part of the sustainable development of rail transit construction and operation. With the large-scale ...As a long-term strategic policy of Chinas social and economic development, energy conservation is also an important part of the sustainable development of rail transit construction and operation. With the large-scale construction and opening and operation of domestic rail transit, rail transit has become a major energy consumption in various cities, and energy saving is imminent, and should be paid attention to for a long time. Starting from the operation organization of the rail transit, the relevant measures for the energy saving operation of the rail transit train are initially explored, and the energy saving measures of the traffic organization are put forward from many aspects and angles. However, due to the limitations of rail transit energy consumption measurement and equipment and related data accumulation, the energy saving effect of various driving organization measures cannot be quantitatively analyzed.展开更多
The growing demand for capacity has prompted the rail industry to explore next-generation train control systems,such as train autonomous operation control systems,which transmit real-time information between trains wi...The growing demand for capacity has prompted the rail industry to explore next-generation train control systems,such as train autonomous operation control systems,which transmit real-time information between trains with the help of train-to-train communication.The communication delay affects the operation of the system.In addition,the train monitors real-time traffic information through on-board sensors.However,no measurement can be perfect,including sensors,which are affected by factors such as railway geometry and weather conditions.The sensor detection error is uncertain,resulting in multiple information uncertainties.Therefore,this paper proposes a train-following model based on the full velocity difference model by considering multiple information uncertainties and communication delay time to describe the autonomous operation of the train under a train autonomous operation control system.Based on this trainfollowing model,a stability analysis and numerical simulation of train traffic flow are carried out.The results show that when the velocity measured by the sensor is smaller than the real velocity or the headway monitored by the sensor is greater than the real headway,the delay will increase and continue to propagate and accumulate backward,resulting in blockage.Otherwise,the opposite occurs.These findings suggest that the effects of multiple information uncertainties are two-sided,depending on the degree of uncertainty of velocity information and headway information.In addition,communication delay time has little effect on train flow and delay.展开更多
In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based po...In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.展开更多
Bridges,tunnels,cuttings and high subgrade account for a relatively large proportion in China’s heavy-haul railway system,where 10000 t of unit trains and 20000 t of combined trains are in operation.When a train oper...Bridges,tunnels,cuttings and high subgrade account for a relatively large proportion in China’s heavy-haul railway system,where 10000 t of unit trains and 20000 t of combined trains are in operation.When a train operation accident occurs,it can easily cause vehicle intrusions,slant-span lines,tipping and stacking.Based on the viewpoint of system engineering,rescue methods such as hoisting,lifting,pulling and overturning are integrated,according to the characteristics of heavy-haul transport and the construction practice of train accident rescue system.A scheme of technical research and equipment configuration relating to heavy-haul railway rescue in China is put forward based on the situation—embankment,bridge,tunnel(including cuttings),ramp and curve rescue,and so on—and three-dimensional finite-element modelling and calculation checks on the key components are carried out.展开更多
To realize a better automatic train driving operation control strategy for urban rail trains,an automatic train driving method with improved DQN algorithm(classical deep reinforcement learning algorithm)is proposed as...To realize a better automatic train driving operation control strategy for urban rail trains,an automatic train driving method with improved DQN algorithm(classical deep reinforcement learning algorithm)is proposed as a research object.Firstly,the train control model is established by considering the train operation requirements.Secondly,the dueling network and DDQN ideas are introduced to prevent the value function overestimation problem.Finally,the priority experience playback and“restricted speed arrival time”are used to reduce the useless experience utilization.The experiments are carried out to verify the train operation strategy method by simulating the actual line conditions.From the experimental results,the train operation meets the ATO requirements,the energy consumption is 15.75%more energy-efficient than the actual operation,and the algorithm convergence speed is improved by about 37%.The improved DQN method not only enhances the efficiency of the algorithm but also forms a more effective operation strategy than the actual operation,thereby contributing meaningfully to the advancement of automatic train operation intelligence.展开更多
East Japan Railway Company(JR East)is aiming to“realize driverless train operation”as one of the key measures to respond to rapid changes in the business environment.Currently,Automatic Train Operation(ATO)equipment...East Japan Railway Company(JR East)is aiming to“realize driverless train operation”as one of the key measures to respond to rapid changes in the business environment.Currently,Automatic Train Operation(ATO)equipment is not installed on the Shinkansen,but there are plans to introduce ATO or driverless operation in the near future.From 2018-2021,the Ministry of Land,Infrastructure,Transport and Tourism(MLIT)held the“ATO Technology Study Group for Railways”in which the concept of technical requirements necessary for driverless operation was discussed.In 2021,JR East conducted the GOA4 demonstration test on the Joetsu Shinkansen.In this test,we were able to confirm the basic functions of Shinkansen vehicles such as automatic departure control,speed control,fixed position stop control,and remote stop control using ATO.We aim to realize unattended operation(GOA4)for deadhead trains between Niigata Station and the Niigata Shinkansen Rolling Stock Center by the end of the 2020 s,and driverless operation(GOA3)for passenger trains of the Joetsu Shinkansen by the mid-2030s and continue to develop the necessary technologies and build systems.展开更多
Bridges crossing active faults are more likely to suffer serious damage or even collapse due to the wreck capabilities of near-fault pulses and surface ruptures under earthquakes.Taking a high-speed railway simply-sup...Bridges crossing active faults are more likely to suffer serious damage or even collapse due to the wreck capabilities of near-fault pulses and surface ruptures under earthquakes.Taking a high-speed railway simply-supported girder bridge with eight spans crossing an active strike-slip fault as the research object,a refined coupling dynamic model of the high-speed train-CRTS III slab ballastless track-bridge system was established based on ABAQUS.The rationality of the established model was thoroughly discussed.The horizontal ground motions in a fault rupture zone were simulated and transient dynamic analyses of the high-speed train-track-bridge coupling system under 3-dimensional seismic excitations were subsequently performed.The safe running speed limits of a high-speed train under different earthquake levels(frequent occurrence,design and rare occurrence)were assessed based on wheel-rail dynamic(lateral wheel-rail force,derailment coefficient and wheel-load reduction rate)and rail deformation(rail dislocation,parallel turning angle and turning angle)indicators.Parameter optimization was then investigated in terms of the rail fastener stiffness and isolation layer friction coefficient.Results of the wheel-rail dynamic indicators demonstrate the safe running speed limits for the high-speed train to be approximately 200 km/h and 80 km/h under frequent and design earthquakes,while the train is unable to run safely under rare earthquakes.In addition,the rail deformations under frequent,design and rare earthquakes meet the safe running requirements of the high-speed train for the speeds of 250,100 and 50 km/h,respectively.The speed limits determined for the wheel-rail dynamic indicators are lower due to the complex coupling effect of the train-track-bridge system under track irregularity.The running safety of the train was improved by increasing the fastener stiffness and isolation layer friction coefficient.At the rail fastener lateral stiffness of 60 kN/mm and isolation layer friction coefficients of 0.9 and 0.8,respectively,the safe running speed limits of the high-speed train increased to 250 km/h and 100 km/h under frequent and design earthquakes,respectively.展开更多
Fastening failures have frequently been found on China high-speed railway curved tracks in recent years.Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyz...Fastening failures have frequently been found on China high-speed railway curved tracks in recent years.Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyzed.A train-curved slab track interaction model is built,in which the real shape of the curved rail is considered and modeled with reduced beam model(RBM)and curved beam theory,and the slabs are modeled with four-nodes Kirchhoff-Love plate elements.The present model is validated at first with different traditional models.Then the influence of fastening failure in curved slab track on train-track interaction dynamics is studied.A different number of failed fastenings is assumed to occur at the curved track,and different types of fastening failure including the fatigue fracture of the clip structure and failure of the rail pad are considered.Based on the calculation results,the fatigue fracture of the clip structure has little influence on train-track interaction dynamics.But when rail pad failure happens and its equivalent vertical stiffness and damping are less than one-tenth of its original,the fastening failure seriously affects the high-speed train operation safety,and it must be prevented.展开更多
Modeling the application of train operation adjustment actions to recover from delays is of great importance to supporting the decision-making of dispatchers.In this study,the effects of two train operation adjustment...Modeling the application of train operation adjustment actions to recover from delays is of great importance to supporting the decision-making of dispatchers.In this study,the effects of two train operation adjustment actions on train delay recovery were explored using train operation records from scheduled and actual train timetables.First,the modeling data were sorted to extract the possible influencing factors under two typical train operation adjustment actions,namely the compression of the train dwell time at stations and the compression of the train running time in sections.Stepwise regression methods were then employed to determine the importance of the influencing factors corresponding to the train delay recovery time,namely the delay time,the scheduled supplement time,the running interval,the occurrence time,and the place where the delay occurred,under the two train operation adjustment actions.Finally,the gradient-boosted regression tree(GBRT)algorithm was applied to construct a delay recovery model to predict the delay recovery effects of the train operation adjustment actions.A comparison of the prediction results of the GBRT model with those of a random forest model confirmed the better performance of the GBRT prediction model.展开更多
<div style="text-align:justify;"> In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics ...<div style="text-align:justify;"> In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm. </div>展开更多
Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signal...Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.展开更多
The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive(e.g. in the case of depot operations) or highly inefficient(e.g. in indust...The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive(e.g. in the case of depot operations) or highly inefficient(e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for lowspeed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.展开更多
With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway ...With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.展开更多
Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between trains.Accurate estimation of these factors is essential to decision-making for train delay...Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between trains.Accurate estimation of these factors is essential to decision-making for train delay reduction,train dispatching,and station capacity estimation.In the present study,we aim to propose a train dwell time model based on an averaging mechanism and dynamic updating to address the challenges in the train dwell time prediction problem(e.g.,dynamics over time,heavy-tailed distribution of data,and spatiotemporal relationships of factors)for real-time train dispatching.The averaging mechanism in the present study is based on multiple state-of-the-art base predictors,enabling the proposed model to integrate the advantages of the base predictors in addressing the challenges in terms of data attributes and data distributions.Then,considering the influence of passenger flow on train dwell time,we use a dynamic updating method based on exponential smoothing to improve the performance of the proposed method by considering the real-time passenger amount fluctuations(e.g.,passenger soars in peak hours or passenger plunges during regular periods).We conduct experiments with the train operation data and passenger flow data from the Chinese high-speed railway line.The results show that due to the advantages over the base predictors,the averaging mechanism can more accurately predict the dwell time at stations than its counterparts for different prediction horizons regarding predictive errors and variances.Further,the experimental results show that dynamic smoothing can significantly improve the accuracy of the proposed model during passenger amount changes,i.e.,15.4%and 15.5%corresponding to the mean absolute error and root mean square error,respectively.Based on the proposed predictor,a feature importance analysis shows that the planned dwell time and arrival delay are the two most important factors to dwell time.However,planned time has positive influences,whereas arrival delay has negative influences.展开更多
BACKGROUND Operative reports(OP-Rs)are essential for communication among healthcare providers.They require accuracy and completeness to serve as a quality indicator of patient care.Objective assessment of primary tota...BACKGROUND Operative reports(OP-Rs)are essential for communication among healthcare providers.They require accuracy and completeness to serve as a quality indicator of patient care.Objective assessment of primary total knee replacement(TKR)OP-Rs has never been reported.Therefore,a standardized benchmark for assessment and factors affecting the completeness of TKR OP-Rs needs to be evaluated.AIM To evaluate the completeness rate of primary TKR OP-Rs in a teaching hospital and to assess the factors affecting completeness.METHODS A retrospective review of 58 consecutive primary TKR OP-Rs in a tertiary te-aching hospital were included in this study.We used document analysis to review the OP-Rs against a standardized list of six subsets of mandatory variables.The correlation between the percentage of completeness and the specific variables was determined.RESULTS After analyzing 58 cases,we found that the time to documentation was 1.5 hours.Out of the 52 mandatory variables,a median of 30 variables were documented yielding a completeness of 58%.Administrative,procedural,exposure,and im-plant variables were documented the most often,whereas clinical and process variables were most frequently left uncompleted.The documentation of the operative maneuver was variable.There was no association between the com-pleteness of the reports and the time to documentation,documenter level,com-plication rate,operative duration,or length of hospital stay.CONCLUSION Multiple variables were left undocumented on the unstructured primary TKR OP-Rs.The completeness percentage will likely improve after the implementation of a standardized structured OP-R.展开更多
基金supported by National Natural Science Foundation of China and High Speed Railway Union Foundation of China(No.U11344205)
文摘This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control input. The ATSMC structure is designed by considering the nonlinear characteristics of the dynamic model and the parametric uncertainties of the train operation in real time. A nonsingular terminal sliding mode control is employed to make the system quickly reach a stable state within a finite time, which makes the control input less adjust to guarantee the riding comfort. An adaptive mechanism is used to estimate controller parameters to get rid of the need of the prior knowledge about the bounds of system uncertainty. Simulations are presented to demonstrate the effectiveness of the proposed controller, which has robust performance to deal with the external disturbance and system parametric uncertainties. Thereby, the system guarantees the train operation to be accurate and comfortable.
文摘The determination and optimization of Automatic Train Operation(ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider many goals of the train operation, such as safety, accuracy, comfort, energy saving and so on. This paper designs a set of efficient and universal multi-objective control strategy. Firstly, based on the analysis of urban rail transit and its operating environment, the multi-objective optimization model considering all the indexes of train operation is established by using multi-objective optimization theory. Secondly, Non-dominated Sorting Genetic Algorithm II(NSGA-II) is used to solve the model, and the optimal speed curve of train running is generated.Finally, the intelligent controller is designed by the combination of fuzzy controller algorithm and the predictive control algorithm, which can control and optimize the train operation in real time. Then the robustness of the control system can ensure and the requirements for multi-objective in train operation can be satisfied.
基金funded by the National Natural Science Foundation of China(71701216,71171200).
文摘Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.Design/methodology/approach–The authors optimize the train operational plan in a special network layout,i.e.an urban rail corridor with dead-end terminal yard,by decomposing it into two sub-problems:train timetable optimization and rolling stock circulation optimization.As for train timetable optimization,the authors propose a schedule-based passenger flow assignment method,construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm.For the optimization of rolling stock circulation,the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.Findings–The case study shows that the train operational plan developed by the study’s approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.Originality/value–The example verifies the efficiency of the model and algorithm.
文摘The research background is based on great consumption of urban rail transit energy, through summarizing the research of scholars at home and abroad, the comprehensive research including train operation pattern, the train traction characteristics and optimization design of integrated research has carried out in this paper, by using OPENTRACK software simulation to verify the optimization results according to different line features finally. The aim of this paper is to explore ways and methods of traction strategy optimization under the condition of trains timing energy saving. The main research contents of this paper are based on the research status at home and abroad, first of all, the different operating modes of the train running on the line are analysed, including the time saving mode, the energy saving mode and timing energy saving mode, and quantitative analysed the influence of different operation modes on vehicle energy consumption. The influence factors and traction calculation method of energy consumption of train running are studied. Firstly, the factors that affect the energy consumption of the train are analysed, including the basic facilities and transport organization mode. On the basis of this, the train load and running status of the train are analysed, and the model of the train movement and energy consumption are calculated. The OPENTRACK software is used to establish the actual circuit model, and the simulation is verified. The results show that the reasonable operation mode of the train operation mode can greatly reduce the energy consumption.
基金This work was supported by the Youth Backbone Teachers Training Program of Henan Colleges and Universities under Grant No.2016ggjs-287the Project of Science and Technology of Henan Province under Grant Nos.172102210124 and 202102210269.
文摘A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme,and the initial population can be formed by the way.The fitness function can be designed by the design requirements of the train control stop error,time error and energy consumption.the effectiveness of new individual can be ensured by checking the validity of the original individual when its in the process of selection,crossover and mutation,and the optimal algorithm will be joined all the operators to make the new group not eliminate on the best individual of the last generation.The simulation result shows that the proposed genetic algorithm comparing with the optimized multi-particle simulation model can reduce more than 10%energy consumption,it can provide a large amount of sub-optimal solution and has obvious optimization effect.
文摘As a long-term strategic policy of Chinas social and economic development, energy conservation is also an important part of the sustainable development of rail transit construction and operation. With the large-scale construction and opening and operation of domestic rail transit, rail transit has become a major energy consumption in various cities, and energy saving is imminent, and should be paid attention to for a long time. Starting from the operation organization of the rail transit, the relevant measures for the energy saving operation of the rail transit train are initially explored, and the energy saving measures of the traffic organization are put forward from many aspects and angles. However, due to the limitations of rail transit energy consumption measurement and equipment and related data accumulation, the energy saving effect of various driving organization measures cannot be quantitatively analyzed.
基金supported by Beijing Natural Science Foundation(Grant No.L231009)the National Natural Science Foundation of China(Grant No.72288101)the Fundamental Research Funds for the Central Universities(Grant No.2022JBZY017)。
文摘The growing demand for capacity has prompted the rail industry to explore next-generation train control systems,such as train autonomous operation control systems,which transmit real-time information between trains with the help of train-to-train communication.The communication delay affects the operation of the system.In addition,the train monitors real-time traffic information through on-board sensors.However,no measurement can be perfect,including sensors,which are affected by factors such as railway geometry and weather conditions.The sensor detection error is uncertain,resulting in multiple information uncertainties.Therefore,this paper proposes a train-following model based on the full velocity difference model by considering multiple information uncertainties and communication delay time to describe the autonomous operation of the train under a train autonomous operation control system.Based on this trainfollowing model,a stability analysis and numerical simulation of train traffic flow are carried out.The results show that when the velocity measured by the sensor is smaller than the real velocity or the headway monitored by the sensor is greater than the real headway,the delay will increase and continue to propagate and accumulate backward,resulting in blockage.Otherwise,the opposite occurs.These findings suggest that the effects of multiple information uncertainties are two-sided,depending on the degree of uncertainty of velocity information and headway information.In addition,communication delay time has little effect on train flow and delay.
基金Project(52272339)supported by the National Natural Science Foundation of ChinaProject(2023YFB390730303)supported by the National Key Research and Development Program of China+2 种基金Project(L2023G004)supported by the Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.Project(QZKFKT2023-005)supported by the State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive,ChinaProject(2022JZZ05)supported by the Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway(Central South University),China。
文摘In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.
文摘Bridges,tunnels,cuttings and high subgrade account for a relatively large proportion in China’s heavy-haul railway system,where 10000 t of unit trains and 20000 t of combined trains are in operation.When a train operation accident occurs,it can easily cause vehicle intrusions,slant-span lines,tipping and stacking.Based on the viewpoint of system engineering,rescue methods such as hoisting,lifting,pulling and overturning are integrated,according to the characteristics of heavy-haul transport and the construction practice of train accident rescue system.A scheme of technical research and equipment configuration relating to heavy-haul railway rescue in China is put forward based on the situation—embankment,bridge,tunnel(including cuttings),ramp and curve rescue,and so on—and three-dimensional finite-element modelling and calculation checks on the key components are carried out.
文摘To realize a better automatic train driving operation control strategy for urban rail trains,an automatic train driving method with improved DQN algorithm(classical deep reinforcement learning algorithm)is proposed as a research object.Firstly,the train control model is established by considering the train operation requirements.Secondly,the dueling network and DDQN ideas are introduced to prevent the value function overestimation problem.Finally,the priority experience playback and“restricted speed arrival time”are used to reduce the useless experience utilization.The experiments are carried out to verify the train operation strategy method by simulating the actual line conditions.From the experimental results,the train operation meets the ATO requirements,the energy consumption is 15.75%more energy-efficient than the actual operation,and the algorithm convergence speed is improved by about 37%.The improved DQN method not only enhances the efficiency of the algorithm but also forms a more effective operation strategy than the actual operation,thereby contributing meaningfully to the advancement of automatic train operation intelligence.
文摘East Japan Railway Company(JR East)is aiming to“realize driverless train operation”as one of the key measures to respond to rapid changes in the business environment.Currently,Automatic Train Operation(ATO)equipment is not installed on the Shinkansen,but there are plans to introduce ATO or driverless operation in the near future.From 2018-2021,the Ministry of Land,Infrastructure,Transport and Tourism(MLIT)held the“ATO Technology Study Group for Railways”in which the concept of technical requirements necessary for driverless operation was discussed.In 2021,JR East conducted the GOA4 demonstration test on the Joetsu Shinkansen.In this test,we were able to confirm the basic functions of Shinkansen vehicles such as automatic departure control,speed control,fixed position stop control,and remote stop control using ATO.We aim to realize unattended operation(GOA4)for deadhead trains between Niigata Station and the Niigata Shinkansen Rolling Stock Center by the end of the 2020 s,and driverless operation(GOA3)for passenger trains of the Joetsu Shinkansen by the mid-2030s and continue to develop the necessary technologies and build systems.
基金Project(51378050) supported by the National Natural Science Foundation of ChinaProject(B13002) supported by the “111” Project,China+2 种基金Project (8192035) supported by the Beijing Municipal Natural Science Foundation,ChinaProject(P2019G002) supported by the Science and Technology Research and Development Program of China RailwayProject(2019YJ193) supported by the State Key Laboratory for Track Technology of High-speed Railway,China。
文摘Bridges crossing active faults are more likely to suffer serious damage or even collapse due to the wreck capabilities of near-fault pulses and surface ruptures under earthquakes.Taking a high-speed railway simply-supported girder bridge with eight spans crossing an active strike-slip fault as the research object,a refined coupling dynamic model of the high-speed train-CRTS III slab ballastless track-bridge system was established based on ABAQUS.The rationality of the established model was thoroughly discussed.The horizontal ground motions in a fault rupture zone were simulated and transient dynamic analyses of the high-speed train-track-bridge coupling system under 3-dimensional seismic excitations were subsequently performed.The safe running speed limits of a high-speed train under different earthquake levels(frequent occurrence,design and rare occurrence)were assessed based on wheel-rail dynamic(lateral wheel-rail force,derailment coefficient and wheel-load reduction rate)and rail deformation(rail dislocation,parallel turning angle and turning angle)indicators.Parameter optimization was then investigated in terms of the rail fastener stiffness and isolation layer friction coefficient.Results of the wheel-rail dynamic indicators demonstrate the safe running speed limits for the high-speed train to be approximately 200 km/h and 80 km/h under frequent and design earthquakes,while the train is unable to run safely under rare earthquakes.In addition,the rail deformations under frequent,design and rare earthquakes meet the safe running requirements of the high-speed train for the speeds of 250,100 and 50 km/h,respectively.The speed limits determined for the wheel-rail dynamic indicators are lower due to the complex coupling effect of the train-track-bridge system under track irregularity.The running safety of the train was improved by increasing the fastener stiffness and isolation layer friction coefficient.At the rail fastener lateral stiffness of 60 kN/mm and isolation layer friction coefficients of 0.9 and 0.8,respectively,the safe running speed limits of the high-speed train increased to 250 km/h and 100 km/h under frequent and design earthquakes,respectively.
基金This work was supported by the National Natural Science Foundation of China(Grant No.12072293)the Project of State Key Laboratory of Traction Power for Southwest Jiaotong University(Grant No.2021TPL-T10)+2 种基金China Scholarship Council(Grant No.202007000115)the Key Scientific Research Fund Project of Sichuan Education Department(Grant No.18ZA0454)the Key Research Program of Xihua University(Grant No.Z1020212).
文摘Fastening failures have frequently been found on China high-speed railway curved tracks in recent years.Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyzed.A train-curved slab track interaction model is built,in which the real shape of the curved rail is considered and modeled with reduced beam model(RBM)and curved beam theory,and the slabs are modeled with four-nodes Kirchhoff-Love plate elements.The present model is validated at first with different traditional models.Then the influence of fastening failure in curved slab track on train-track interaction dynamics is studied.A different number of failed fastenings is assumed to occur at the curved track,and different types of fastening failure including the fatigue fracture of the clip structure and failure of the rail pad are considered.Based on the calculation results,the fatigue fracture of the clip structure has little influence on train-track interaction dynamics.But when rail pad failure happens and its equivalent vertical stiffness and damping are less than one-tenth of its original,the fastening failure seriously affects the high-speed train operation safety,and it must be prevented.
基金the National Nature Science Foundation of China(Nos.71871188 and U1834209)the Science and Technology Department of Sichuan Province(No.2018JY0567)。
文摘Modeling the application of train operation adjustment actions to recover from delays is of great importance to supporting the decision-making of dispatchers.In this study,the effects of two train operation adjustment actions on train delay recovery were explored using train operation records from scheduled and actual train timetables.First,the modeling data were sorted to extract the possible influencing factors under two typical train operation adjustment actions,namely the compression of the train dwell time at stations and the compression of the train running time in sections.Stepwise regression methods were then employed to determine the importance of the influencing factors corresponding to the train delay recovery time,namely the delay time,the scheduled supplement time,the running interval,the occurrence time,and the place where the delay occurred,under the two train operation adjustment actions.Finally,the gradient-boosted regression tree(GBRT)algorithm was applied to construct a delay recovery model to predict the delay recovery effects of the train operation adjustment actions.A comparison of the prediction results of the GBRT model with those of a random forest model confirmed the better performance of the GBRT prediction model.
文摘<div style="text-align:justify;"> In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm. </div>
基金This research was jointly supported by the National Natural Science Foundation of China[Grant 62203468]the Young Elite Scientist Sponsorship Program by China Association for Science and Technology(CAST)[Grant 2022QNRC001]+1 种基金the Technological Research and Development Program of China Railway Corporation Limited[Grant K2021X001]by the Foundation of China Academy of Railway Sciences Corporation Limited[Grant 2021YJ043].On behalf all authors,the corresponding author states that there is no conflict of interest.
文摘Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.
基金funding of the SAMIRA project by the European Regional Development Fund under grant number 0801689
文摘The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive(e.g. in the case of depot operations) or highly inefficient(e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for lowspeed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.
文摘With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.
基金This work was supported by the National Natural Science Foundation of China(No.71871188).
文摘Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between trains.Accurate estimation of these factors is essential to decision-making for train delay reduction,train dispatching,and station capacity estimation.In the present study,we aim to propose a train dwell time model based on an averaging mechanism and dynamic updating to address the challenges in the train dwell time prediction problem(e.g.,dynamics over time,heavy-tailed distribution of data,and spatiotemporal relationships of factors)for real-time train dispatching.The averaging mechanism in the present study is based on multiple state-of-the-art base predictors,enabling the proposed model to integrate the advantages of the base predictors in addressing the challenges in terms of data attributes and data distributions.Then,considering the influence of passenger flow on train dwell time,we use a dynamic updating method based on exponential smoothing to improve the performance of the proposed method by considering the real-time passenger amount fluctuations(e.g.,passenger soars in peak hours or passenger plunges during regular periods).We conduct experiments with the train operation data and passenger flow data from the Chinese high-speed railway line.The results show that due to the advantages over the base predictors,the averaging mechanism can more accurately predict the dwell time at stations than its counterparts for different prediction horizons regarding predictive errors and variances.Further,the experimental results show that dynamic smoothing can significantly improve the accuracy of the proposed model during passenger amount changes,i.e.,15.4%and 15.5%corresponding to the mean absolute error and root mean square error,respectively.Based on the proposed predictor,a feature importance analysis shows that the planned dwell time and arrival delay are the two most important factors to dwell time.However,planned time has positive influences,whereas arrival delay has negative influences.
文摘BACKGROUND Operative reports(OP-Rs)are essential for communication among healthcare providers.They require accuracy and completeness to serve as a quality indicator of patient care.Objective assessment of primary total knee replacement(TKR)OP-Rs has never been reported.Therefore,a standardized benchmark for assessment and factors affecting the completeness of TKR OP-Rs needs to be evaluated.AIM To evaluate the completeness rate of primary TKR OP-Rs in a teaching hospital and to assess the factors affecting completeness.METHODS A retrospective review of 58 consecutive primary TKR OP-Rs in a tertiary te-aching hospital were included in this study.We used document analysis to review the OP-Rs against a standardized list of six subsets of mandatory variables.The correlation between the percentage of completeness and the specific variables was determined.RESULTS After analyzing 58 cases,we found that the time to documentation was 1.5 hours.Out of the 52 mandatory variables,a median of 30 variables were documented yielding a completeness of 58%.Administrative,procedural,exposure,and im-plant variables were documented the most often,whereas clinical and process variables were most frequently left uncompleted.The documentation of the operative maneuver was variable.There was no association between the com-pleteness of the reports and the time to documentation,documenter level,com-plication rate,operative duration,or length of hospital stay.CONCLUSION Multiple variables were left undocumented on the unstructured primary TKR OP-Rs.The completeness percentage will likely improve after the implementation of a standardized structured OP-R.
