Considering the development of urban freight transport,this paper presents an operational strategy for freight transport based on the urban metro system.To improve the alignment between service capacity and transport ...Considering the development of urban freight transport,this paper presents an operational strategy for freight transport based on the urban metro system.To improve the alignment between service capacity and transport demand under passenger and freight co-transportation(PFCT),a mixed-integer nonlinear programming model(MINLP)is developed to simultaneously optimize the train timetable(TT)and rolling stock circulation plan(RSCP),with particular consideration of flexible train composition mode and skip-stop strategies.Moreover,by introducing allocation rules for passengers and freight,the tripartite interests of operators,passengers,and freight agents are synergistically considered in the proposed model.To facilitate the model solution,a variable neighborhood search(VNS)algorithm is designed for the generation of high-quality solutions in a reasonable computational time.Finally,based on a simplified example and empirical data from the Beijing Metro Yizhuang Line,several sets of numerical examples are implemented to validate the applicability and effectiveness of the model and the approach.展开更多
Trains are prone to delays and deviations from train operation plans during their operation because of internal or external disturbances. Delays may develop into operational conflicts between adjacent trains as a resu...Trains are prone to delays and deviations from train operation plans during their operation because of internal or external disturbances. Delays may develop into operational conflicts between adjacent trains as a result of delay propagation, which may disturb the arrangement of the train operation plan and threaten the operational safety of trains. Therefore, reliable conflict prediction results can be valuable references for dispatchers in making more efficient train operation adjustments when conflicts occur. In contrast to the traditional approach to conflict prediction that involves introducing random disturbances, this study addresses the issue of the fuzzification of time intervals in a train timetable based on historical statistics and the modeling of a high-speed railway train timetable based on the concept of a timed Petri net. To measure conflict prediction results more comprehensively, we divided conflicts into potential conflicts and certain conflicts and defined the judgment conditions for both. Two evaluation indexes, one for the deviation of a single train and one for the possibility of conflicts between adjacent train operations, were developed using a formalized computation method. Based on the temporal fuzzy reasoning method, with some adjustment, a new conflict prediction method is proposed, and the results of a simulation example for two scenarios are presented. The results prove that conflict prediction after fuzzy processing of the time intervals of a train timetable is more reliable and practical and can provide helpful information for use in train operation adjustment, train timetable improvement, and other purposes.展开更多
Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway system.In such cases,train timetables need to be rescheduled.However,timely and efficient train timetable resc...Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway system.In such cases,train timetables need to be rescheduled.However,timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization efficiency.This paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based decisionmaking.Firstly,the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer,providing the better understanding of overall operation in the high-speed railway system.Then,a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast convergence.Extensive experiments on various delay scenarios are conducted.The results demonstrate the effectiveness of the proposed method in comparison to other popular methods.展开更多
According to the pathological process of ischemic apoplexy, which involves its onset and development, this paper expounds the great significance of adopting various active and effective measures within the therapeutic...According to the pathological process of ischemic apoplexy, which involves its onset and development, this paper expounds the great significance of adopting various active and effective measures within the therapeutic timetable for favorable prognosis and improvement of apoplexy. The author’s viewpoints differ from the conventional thinking towards the management of apoplexy, stressing super early intervention with acupuncture.展开更多
The rapid growth of passenger flow in urban rail transit has led to great service pressures for metro companies in organizing train services to provide higher transportation capacities in order to satisfy passengers&#...The rapid growth of passenger flow in urban rail transit has led to great service pressures for metro companies in organizing train services to provide higher transportation capacities in order to satisfy passengers' travel demand, especially on those metro lines with insufficient rolling stock. In order to cope with high passenger flow service pressure, a mixed integer nonlinear programming(MINLP) model is proposed to optimize the line plan, timetable and rolling stock circulation simultaneously, to reduce the number of rolling stocks and increase the number of full-length services. A two-step algorithm strategy is proposed. In the first stage, the train timetable is optimized under the assumption that all the train services are the full-length services. In the second stage, the rolling stock plan is optimized based on the timetable optimized in the first stage. To ensure a feasible rolling stock circulation, certain full-length services are shortened to the short-length services due to the limited number of rolling stocks. Numerical experiments are performed based on the real-life data of Shanghai Metro Line 8. Results show that the proposed method can efficiently optimize the timetable and rolling stock circulation of the whole operation day. The optimized results are beneficial for both the service and the operational costs.展开更多
Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimi...Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway,the minimum headway and the latest end-of-operation time.The objective of the model is to maximize the number of reachable passengers in the end-of-operation period.A solution method based on a preset train service is proposed,which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.Findings-The results of the case study of Wuhan Metro show that the solution method can obtain highquality solutions in a shorter time;and the shorter the time interval of passenger flow data,the more obvious the advantage of solution speed;after optimization,the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.Originality/value-Existing research results only consider the passengers who take the last train.Compared with previous research,considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination.Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network,but due to the decrease in passenger demand,postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.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
This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can...This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.展开更多
Metro plays a vital role in managing passenger distribution at intercity railway(IR)sta-tions,particularly during holidays when there is a surge in tourist traffic.To efficiently accommodate the high demand for interc...Metro plays a vital role in managing passenger distribution at intercity railway(IR)sta-tions,particularly during holidays when there is a surge in tourist traffic.To efficiently accommodate the high demand for intercity travel,it becomes imperative for metro agen-cies to optimize holiday timetables.This paper focuses on designing holiday timetables of the first service period for the metro network that connects to an IR station,aiming to enhance multimodal collaboration with IR timetables while ensuring seamless coordina-tion among various metro lines at the network level.A bi-objective model is proposed to maximize the temporal availability of metro network and minimize transfer waiting times for IR passengers traveling in early morning.To solve the model,an improved artificial bee colony algorithm(ABC)is designed,incorporating adaptive neighbour search and simu-lated annealing techniques.The effectiveness of the model and algorithm is verified using the Shanghai metro network and Hongqiao Railway Station.Results indicate a 9.46%increase in the temporal availability of metro network for IR passengers,coupled with a 9.68%reduction in passenger transfer waiting times.Notably,the study reveals that solely advancing operations of the IR-connected metro lines is inefficient.Instead,optimizing train timetables for the entire metro network proves to be a cost-effective approach to enhancing the overall service level of early-morning operations.Furthermore,the study emphasizes the significance of even-numbered train headways in reducing passenger transfer waiting times.展开更多
In northern China,university classrooms are often densely populated,and students have limited means of thermal adaptation during lectures.Considering the significant differences in the thermal environment of the class...In northern China,university classrooms are often densely populated,and students have limited means of thermal adaptation during lectures.Considering the significant differences in the thermal environment of the classroom throughout different periods,changing the patterns of classroom utilization is a feasible way to improve students’thermal comfort during classes and ensure learning efficiency.A university teaching building in Xi’an is considered an example in this study.The indoor and outdoor thermal environment parameters of the teaching building were measured in the autumn semester,and the students’thermal sensation was investigated.On this basis,a model for optimizing university timetables was developed to minimize students’thermal discomfort in classrooms.The study results showed:1)During non-heating seasons,students felt comfortable in all periods,except for the third class period(14:00-15:30),during which they felt slightly hot.During the heating season,students felt slightly cold in the first class period(8:30-10:00),slightly hot in the third class period,and comfortable in the second(10:30-12:00)and fourth(16:00-17:30)class periods.2)Compared to the general schedule,the optimized timetable decreased first period classes by 14 and increased fourth period classes by 13,with minimal changes elsewhere.Adopting this approach,students’thermal discomfort time during classes in the autumn semester was shortened by 6.16%.3)The students’thermal discomfort time reduction rate obtained by timetabling optimization during the non-heating season,heating season are 0.78%,8.91%,respectively.The effect of reducing students’thermal discomfort is more pronounced during the heating season.展开更多
This paper addresses the energy conservation challenge in metro systems during the first service period,characterized by large train headways and low passenger demands.A novel train timetabling method incorporating an...This paper addresses the energy conservation challenge in metro systems during the first service period,characterized by large train headways and low passenger demands.A novel train timetabling method incorporating an express-local mode is proposed to maximize the overlap time between accelerating and braking trains,thereby facilitating the utiliza-tion of regenerative braking energy(RBE).Local and express trains depart alternately,with skip-stop strategies implemented for express trains.Considering the interests of operators and passengers for energy and travel time savings,a bi-objective model is proposed to jointly optimize train timetable and stopping plan.The non-dominated sorting genetic algorithm II(NSGA-II)is applied to solve the model and obtain Pareto optimal solutions.Numerical experiments based on Ningbo Metro Line 1 data validate the effectiveness of proposed methods,showcasing significant enhancement in RBE utilization and notable reduction in passenger travel time.The proposed express-local mode establishes stable tracking relationships within train pairs,ensuring effective RBE utilization.Comparative analyses reveal that deadheading is more effective than flexible skip-stop for energy-efficient and time-saving metro operations.展开更多
This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and ...This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.展开更多
This study investigates the use of autonomous vehicles in bus rapid transit lanes during the initial phases of autonomous driving development.The aim is to accelerate the advancement of autonomous driving technologies...This study investigates the use of autonomous vehicles in bus rapid transit lanes during the initial phases of autonomous driving development.The aim is to accelerate the advancement of autonomous driving technologies and enhance the efficiency of bus lane usage.We first develop a dynamic joint optimization model that adjusts autonomous vehicle speeds and bus timetables to minimize vehicle travel times while reducing bus passenger waiting times.We account for random variables such as stochastic passenger arrivals at bus stations and variable demand for autonomous vehicle travel by constructing a stochastic dynamic model.To address the computational challenges of large-scale scenarios,we implement a simulation-based heuristic algorithm framework.This framework is designed to efficiently produce high-quality solutions within feasible time limits.Our numerical studies on an actual bus line show that our approach significantly improves system throughput compared to existing benchmarks.Moreover,by strategically managing the entry of autonomous vehicles into the lane and modifying bus timetables,we further enhance the operational efficiency of the system.展开更多
MOHURD released the Notice on Accelerating the Household Garbage Sorting in Certain Key Cities,requiring pushing forward the household garbage sorting in 46 key cities such as Beijing,Tianjin,Shanghai,etc.,and establi...MOHURD released the Notice on Accelerating the Household Garbage Sorting in Certain Key Cities,requiring pushing forward the household garbage sorting in 46 key cities such as Beijing,Tianjin,Shanghai,etc.,and establishing demonstration areas for garbage sorting in these cities for 2018.展开更多
At certain urban rail transit(URT)stations,large events,emergencies,or holidays often cause a rapid surge in passenger flow,referred to as large passenger flow(LPF)events.The passenger congestion will spread quickly v...At certain urban rail transit(URT)stations,large events,emergencies,or holidays often cause a rapid surge in passenger flow,referred to as large passenger flow(LPF)events.The passenger congestion will spread quickly via transfer stations and affect other stations and lines in the URT network.This study develops a timetable rescheduling and coordinating method for the URT network under LPF events.Firstly,a collaborative adjustment model of train timetables with a backup-vehicle strategy is formulated to simultaneously consider rescheduling and coordinating problems,to reduce the congestion influence for a URT network.Then,a rolling horizon approach is developed to divide the whole adjustment problem into several decision-making stages to ensure solution efficiency.In each decision-making stage,the influence of LPF propagation within the URT network is firstly evaluated.Based on the congestion evaluation results,the proposed method determines whether it is necessary to adjust timetables of the LPF line or other lines.The proposed method is applied to the Xi’an Metro network in China.The results indicate that the proposed method can effectively evaluate and adjust the train timetables for large URT networks under LPF events.展开更多
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
During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in resc...During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in rescheduling trains,this paper introduces an innovative Human-Computer Interaction framework.This framework enables train dispatchers to propose different timetable adjustment instructions to the original or adjusted timetable.These instructions will be processed,stored,analyzed,and digested by computer program,which finally lead to the modification and calculation of the embedded mathematical model,then a new adjusted timetable will be produced and provided to dispatchers for checking and modifying.This framework can iterate for unlimited times based on dispatchers'intentions,until the final results satisfy them.A demonstration system named RTARS(Real-time Timetable Automatic Rescheduling System)is developed based on this framework and it has been applied in Beijing Railway Administration,which shows its effectiveness in reality.展开更多
Environmental problems have received a great deal of attention in recent years.In particular,CO2 emissions worsen global warming and other environmental problems.The transport sector accounts for 20% of the total CO2 ...Environmental problems have received a great deal of attention in recent years.In particular,CO2 emissions worsen global warming and other environmental problems.The transport sector accounts for 20% of the total CO2 emissions.Therefore,the CO2 emission reduction of the transport sector is of great importance.In order to reduce emissions effectively,it is necessary to change the distribution and transportation processes.The purpose of this study is to minimize both the transportation costs and CO2 emissions during transportation.Our model considers a transportation scheduling problem in which loads are transported from an overseas production base to three domestic demand centers.The need for time-space networks arises naturally to improve the model.It is possible to know the distance carriers are moving,and also consider the timetables of carriers during transportation.Carrier choice,less-than carrier load,and domestic transportation among demand centers are considered as the three target areas to reduce CO2 emissions during the distribution process.The research model was formulated as a mixed integer programming (MIP) problem.It achieves cost reduction,and will contribute to improvement of the natural environment.展开更多
基金supported by the Beijing Natural Science Foundation(9252012)the National Natural Science Foundation of China(72371015,72288101,72431002,and 72161010)Key Laboratory of Railway Industry on Plateau Railway Transportation Intelligent Management and Control(GYYSHZ2301)。
文摘Considering the development of urban freight transport,this paper presents an operational strategy for freight transport based on the urban metro system.To improve the alignment between service capacity and transport demand under passenger and freight co-transportation(PFCT),a mixed-integer nonlinear programming model(MINLP)is developed to simultaneously optimize the train timetable(TT)and rolling stock circulation plan(RSCP),with particular consideration of flexible train composition mode and skip-stop strategies.Moreover,by introducing allocation rules for passengers and freight,the tripartite interests of operators,passengers,and freight agents are synergistically considered in the proposed model.To facilitate the model solution,a variable neighborhood search(VNS)algorithm is designed for the generation of high-quality solutions in a reasonable computational time.Finally,based on a simplified example and empirical data from the Beijing Metro Yizhuang Line,several sets of numerical examples are implemented to validate the applicability and effectiveness of the model and the approach.
文摘Trains are prone to delays and deviations from train operation plans during their operation because of internal or external disturbances. Delays may develop into operational conflicts between adjacent trains as a result of delay propagation, which may disturb the arrangement of the train operation plan and threaten the operational safety of trains. Therefore, reliable conflict prediction results can be valuable references for dispatchers in making more efficient train operation adjustments when conflicts occur. In contrast to the traditional approach to conflict prediction that involves introducing random disturbances, this study addresses the issue of the fuzzification of time intervals in a train timetable based on historical statistics and the modeling of a high-speed railway train timetable based on the concept of a timed Petri net. To measure conflict prediction results more comprehensively, we divided conflicts into potential conflicts and certain conflicts and defined the judgment conditions for both. Two evaluation indexes, one for the deviation of a single train and one for the possibility of conflicts between adjacent train operations, were developed using a formalized computation method. Based on the temporal fuzzy reasoning method, with some adjustment, a new conflict prediction method is proposed, and the results of a simulation example for two scenarios are presented. The results prove that conflict prediction after fuzzy processing of the time intervals of a train timetable is more reliable and practical and can provide helpful information for use in train operation adjustment, train timetable improvement, and other purposes.
基金supported partially by the National Natural Science Foundation of China(61790573,61790575)the Center of National Railway Intelligent Transportation System Engineering and Technology(RITS2019KF03)+3 种基金China Academy of Railway Sciences Corporation LimitedChina Railway Project(N2019G020)China Railway Project(L2022X002)the Key Project of Science and Technology Research Plan of China Academy of Railway Sciences Group Co.Ltd.(2022YJ326)。
文摘Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway system.In such cases,train timetables need to be rescheduled.However,timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization efficiency.This paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based decisionmaking.Firstly,the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer,providing the better understanding of overall operation in the high-speed railway system.Then,a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast convergence.Extensive experiments on various delay scenarios are conducted.The results demonstrate the effectiveness of the proposed method in comparison to other popular methods.
文摘According to the pathological process of ischemic apoplexy, which involves its onset and development, this paper expounds the great significance of adopting various active and effective measures within the therapeutic timetable for favorable prognosis and improvement of apoplexy. The author’s viewpoints differ from the conventional thinking towards the management of apoplexy, stressing super early intervention with acupuncture.
基金Sponsored by the National Key R&D Program of China (Grant No.2021YFB1600100)。
文摘The rapid growth of passenger flow in urban rail transit has led to great service pressures for metro companies in organizing train services to provide higher transportation capacities in order to satisfy passengers' travel demand, especially on those metro lines with insufficient rolling stock. In order to cope with high passenger flow service pressure, a mixed integer nonlinear programming(MINLP) model is proposed to optimize the line plan, timetable and rolling stock circulation simultaneously, to reduce the number of rolling stocks and increase the number of full-length services. A two-step algorithm strategy is proposed. In the first stage, the train timetable is optimized under the assumption that all the train services are the full-length services. In the second stage, the rolling stock plan is optimized based on the timetable optimized in the first stage. To ensure a feasible rolling stock circulation, certain full-length services are shortened to the short-length services due to the limited number of rolling stocks. Numerical experiments are performed based on the real-life data of Shanghai Metro Line 8. Results show that the proposed method can efficiently optimize the timetable and rolling stock circulation of the whole operation day. The optimized results are beneficial for both the service and the operational costs.
基金supported by Talents Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities (Grant No.2021RC228)Special Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities (Grant No.2021YJS103).
文摘Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway,the minimum headway and the latest end-of-operation time.The objective of the model is to maximize the number of reachable passengers in the end-of-operation period.A solution method based on a preset train service is proposed,which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.Findings-The results of the case study of Wuhan Metro show that the solution method can obtain highquality solutions in a shorter time;and the shorter the time interval of passenger flow data,the more obvious the advantage of solution speed;after optimization,the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.Originality/value-Existing research results only consider the passengers who take the last train.Compared with previous research,considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination.Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network,but due to the decrease in passenger demand,postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.
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.
文摘This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.
基金funded by the Natural Science Foundation of Zhejiang Province(No.LY21E080008)the Natural Science Foundation of Ningbo(No.202003N4146)the National Natural Science Foundation of China(No.51408323).
文摘Metro plays a vital role in managing passenger distribution at intercity railway(IR)sta-tions,particularly during holidays when there is a surge in tourist traffic.To efficiently accommodate the high demand for intercity travel,it becomes imperative for metro agen-cies to optimize holiday timetables.This paper focuses on designing holiday timetables of the first service period for the metro network that connects to an IR station,aiming to enhance multimodal collaboration with IR timetables while ensuring seamless coordina-tion among various metro lines at the network level.A bi-objective model is proposed to maximize the temporal availability of metro network and minimize transfer waiting times for IR passengers traveling in early morning.To solve the model,an improved artificial bee colony algorithm(ABC)is designed,incorporating adaptive neighbour search and simu-lated annealing techniques.The effectiveness of the model and algorithm is verified using the Shanghai metro network and Hongqiao Railway Station.Results indicate a 9.46%increase in the temporal availability of metro network for IR passengers,coupled with a 9.68%reduction in passenger transfer waiting times.Notably,the study reveals that solely advancing operations of the IR-connected metro lines is inefficient.Instead,optimizing train timetables for the entire metro network proves to be a cost-effective approach to enhancing the overall service level of early-morning operations.Furthermore,the study emphasizes the significance of even-numbered train headways in reducing passenger transfer waiting times.
基金supported by National Natural Science Foundation of China(52318109)University-Industry Collaborative Education Program(220600551163453)+1 种基金Science and Technology Department of Shaanxi Province(2020SF-393)Shaanxi Province Innovation Capability Support Program-Youth Science and Technology New Star Project(2023KJXX-043).
文摘In northern China,university classrooms are often densely populated,and students have limited means of thermal adaptation during lectures.Considering the significant differences in the thermal environment of the classroom throughout different periods,changing the patterns of classroom utilization is a feasible way to improve students’thermal comfort during classes and ensure learning efficiency.A university teaching building in Xi’an is considered an example in this study.The indoor and outdoor thermal environment parameters of the teaching building were measured in the autumn semester,and the students’thermal sensation was investigated.On this basis,a model for optimizing university timetables was developed to minimize students’thermal discomfort in classrooms.The study results showed:1)During non-heating seasons,students felt comfortable in all periods,except for the third class period(14:00-15:30),during which they felt slightly hot.During the heating season,students felt slightly cold in the first class period(8:30-10:00),slightly hot in the third class period,and comfortable in the second(10:30-12:00)and fourth(16:00-17:30)class periods.2)Compared to the general schedule,the optimized timetable decreased first period classes by 14 and increased fourth period classes by 13,with minimal changes elsewhere.Adopting this approach,students’thermal discomfort time during classes in the autumn semester was shortened by 6.16%.3)The students’thermal discomfort time reduction rate obtained by timetabling optimization during the non-heating season,heating season are 0.78%,8.91%,respectively.The effect of reducing students’thermal discomfort is more pronounced during the heating season.
基金funded by the Natural Science Foundation of Zhejiang Province,China(No.LY21E080008)the Natural Science Foundation of Ningbo of China(No.202003N4146)the National Natural Science Foundation of China(No.51408323).
文摘This paper addresses the energy conservation challenge in metro systems during the first service period,characterized by large train headways and low passenger demands.A novel train timetabling method incorporating an express-local mode is proposed to maximize the overlap time between accelerating and braking trains,thereby facilitating the utiliza-tion of regenerative braking energy(RBE).Local and express trains depart alternately,with skip-stop strategies implemented for express trains.Considering the interests of operators and passengers for energy and travel time savings,a bi-objective model is proposed to jointly optimize train timetable and stopping plan.The non-dominated sorting genetic algorithm II(NSGA-II)is applied to solve the model and obtain Pareto optimal solutions.Numerical experiments based on Ningbo Metro Line 1 data validate the effectiveness of proposed methods,showcasing significant enhancement in RBE utilization and notable reduction in passenger travel time.The proposed express-local mode establishes stable tracking relationships within train pairs,ensuring effective RBE utilization.Comparative analyses reveal that deadheading is more effective than flexible skip-stop for energy-efficient and time-saving metro operations.
基金sponsored in part by the National Natural Science Foundation of China(No.71101109)the Open Fund of the Key Laboratory of Highway Engineering of Ministry of Education,Changsha University of Science & Technology(No.kfj120108)
文摘This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.
文摘This study investigates the use of autonomous vehicles in bus rapid transit lanes during the initial phases of autonomous driving development.The aim is to accelerate the advancement of autonomous driving technologies and enhance the efficiency of bus lane usage.We first develop a dynamic joint optimization model that adjusts autonomous vehicle speeds and bus timetables to minimize vehicle travel times while reducing bus passenger waiting times.We account for random variables such as stochastic passenger arrivals at bus stations and variable demand for autonomous vehicle travel by constructing a stochastic dynamic model.To address the computational challenges of large-scale scenarios,we implement a simulation-based heuristic algorithm framework.This framework is designed to efficiently produce high-quality solutions within feasible time limits.Our numerical studies on an actual bus line show that our approach significantly improves system throughput compared to existing benchmarks.Moreover,by strategically managing the entry of autonomous vehicles into the lane and modifying bus timetables,we further enhance the operational efficiency of the system.
文摘MOHURD released the Notice on Accelerating the Household Garbage Sorting in Certain Key Cities,requiring pushing forward the household garbage sorting in 46 key cities such as Beijing,Tianjin,Shanghai,etc.,and establishing demonstration areas for garbage sorting in these cities for 2018.
基金supported by the National Natural Science Foundation of China(No.U2368216 and 72101184)the Shanghai Science and Technology Program(No.21JC1400600)+2 种基金the Natural Science Foundation of Shanghai(No.23ZR1467400)China Postdoctoral Science Foundation(No.2023M732645)the Shanghai Post-Doctoral Excellence Program(No.2022570).
文摘At certain urban rail transit(URT)stations,large events,emergencies,or holidays often cause a rapid surge in passenger flow,referred to as large passenger flow(LPF)events.The passenger congestion will spread quickly via transfer stations and affect other stations and lines in the URT network.This study develops a timetable rescheduling and coordinating method for the URT network under LPF events.Firstly,a collaborative adjustment model of train timetables with a backup-vehicle strategy is formulated to simultaneously consider rescheduling and coordinating problems,to reduce the congestion influence for a URT network.Then,a rolling horizon approach is developed to divide the whole adjustment problem into several decision-making stages to ensure solution efficiency.In each decision-making stage,the influence of LPF propagation within the URT network is firstly evaluated.Based on the congestion evaluation results,the proposed method determines whether it is necessary to adjust timetables of the LPF line or other lines.The proposed method is applied to the Xi’an Metro network in China.The results indicate that the proposed method can effectively evaluate and adjust the train timetables for large URT networks under LPF events.
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supported by China Railway Research and Development(K2021x001)the Talent Fund of Beijing Jiaotong University(2023JBRC003).
文摘During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in rescheduling trains,this paper introduces an innovative Human-Computer Interaction framework.This framework enables train dispatchers to propose different timetable adjustment instructions to the original or adjusted timetable.These instructions will be processed,stored,analyzed,and digested by computer program,which finally lead to the modification and calculation of the embedded mathematical model,then a new adjusted timetable will be produced and provided to dispatchers for checking and modifying.This framework can iterate for unlimited times based on dispatchers'intentions,until the final results satisfy them.A demonstration system named RTARS(Real-time Timetable Automatic Rescheduling System)is developed based on this framework and it has been applied in Beijing Railway Administration,which shows its effectiveness in reality.
文摘Environmental problems have received a great deal of attention in recent years.In particular,CO2 emissions worsen global warming and other environmental problems.The transport sector accounts for 20% of the total CO2 emissions.Therefore,the CO2 emission reduction of the transport sector is of great importance.In order to reduce emissions effectively,it is necessary to change the distribution and transportation processes.The purpose of this study is to minimize both the transportation costs and CO2 emissions during transportation.Our model considers a transportation scheduling problem in which loads are transported from an overseas production base to three domestic demand centers.The need for time-space networks arises naturally to improve the model.It is possible to know the distance carriers are moving,and also consider the timetables of carriers during transportation.Carrier choice,less-than carrier load,and domestic transportation among demand centers are considered as the three target areas to reduce CO2 emissions during the distribution process.The research model was formulated as a mixed integer programming (MIP) problem.It achieves cost reduction,and will contribute to improvement of the natural environment.
