Automatic Driving Operation Strategy of Urban Rail Train Based on Improved DQN Algorithm

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.

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle.Based on data mechanism models,it predicts the lifespan of key components,evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.Findings-The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system,which helps operators to monitor the operation of vehicle online,predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/value-This system improves the efficiency of rail vehicle operation,scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

Research of BIM Technology in Urban Rail Operation and Maintenance and Application

With the rapid development of urban rail transit,the traditional operation and maintenance methods mainly rely on manpower,and the pressure on equipment operation and maintenance is increasing,and the low work efficiency,high intensity and high operating costs have always been the main problems at this stage.Through BIM visualization technology can effectively solve those problems,the operation and maintenance mode of urban rail signal equipment at this stage is discussed,the integration and visualization of BIM technology are used to make the judgments and early warnings on the maintenance of urban rail signal equipment,and play a positive and important role in operation and maintenance work,this research result can provide ideas and references for urban rail transit operation and maintenance in the new era.

Optimization of train plan for urban rail transit in the multi-routing mode

The train plan of urban rail transit under multi-routing mode can be divided into three parts： train formation, train operation periods and corresponding train counts of each routing in each period. Based on the analysis of passen- ger＇s general travel expenses and operator＇s benefits, the constraints and objective functions are defined and the multiobjective optimization model for the train plan of urban rail transit is presented. Factors considered in the multi- objective optimization model include transport capacity, the requirements of traffic organization, corporation benefits, passenger demands, and passenger choice behavior under multi-train-routing mode. According to the characteristics of this model and practical planning experience, a three-phase solution was designed to gradually optimize the train formarion, train counts as well as operation periods. The instance of Changsha Metro Line 2 validates the feasibility and efficiency of this approach.

Study on Optimization of Urban Rail Train Operation Control Curve Based on Improved Multi-Objective Genetic Algorithm

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.

Analysis of STC Fault in Urban Rail Transit Station of Mobile Block System

Mobile block system is a new type of block technology based on the theory of interval block. This article focuses on the analysis of safety key points, the efficient use of emergency time, the maximum efficiency of mobilizers, to reduce the loss of emergency incidents and casualties.

Optimization method of urban rail train operational plan based on O-D time-varying demand

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.

Future 5G-Oriented System for Urban Rail Transit:Opportunities and Challenges

As a development direction of urban rail transit system,the train autonomous circumambulate system(TACS)can operate in a safer,more efficient,and more economical mode.However,most urban rail transit systems transmit signals through industrial,scientific,and medical(ISM)frequency bands or narrow frequency bands,which cannot meet the requirements of TACS.As a promising solution,the 5th generation(5G)mobile communication provides more services for the future urban rail transit systems,and covers the shortages of exiting communication technologies in terms of capacity and reliability.In this paper,we first briefly review the research status of current train control system and introduce its limitations.Next,we propose a novel network architecture,and present new technologies and requirements of the proposed architecture for TACS.Some potential challenges are then discussed to give insights for further research of TACS.

Estimation method for a skip-stop operation strategy for urban rail transit in China

The skip-stop operation strategy （SOS） is rarely applied to Chinese urban rail transit networks because it is a simple scheme and a less universally popular transportation service. However, the SOS has performance advantages, in that the total trip time can be reduced depending on the number of skipped stations, crowds of passengers can be rapidly evacuated at congested stations in peak periods, and the cost to transit companies is reduced. There is a contradiction between reducing the trip time under the SOS and increasing the passengers＇ waiting times under an all-stop scheme. Given this situation, the three objectives of our study were to minimize the waiting and trip times of all passengers and the travel times of trains. A comprehensive estimation model is presented for the SOS. The mechanism through which the trip time for all passengers is affected by the SOS is analyzed in detail. A 0-I integer programming formulation is established for the three objectives, and is solved using a tabu search algorithm. Finally, an example is presented to demonstrate that the estimation method for the SOS is capable of optimizing the timetable and operation schemes for a Chinese urban rail transit network.

Modified stochastic user-equilibrium assignment algorithm for urban rail transit under network operation

Based on the framework of method of successive averages(MSA), a modified stochastic user-equilibrium assignment algorithm was proposed, which can be used to calculate the passenger flow distribution of urban rail transit(URT) under network operation. In order to describe the congestion's impact to passengers' route choices, a generalized cost function with in-vehicle congestion was set up. Building on the k-th shortest path algorithm, a method for generating choice set with time constraint was embedded, considering the characteristics of network operation. A simple but efficient route choice model, which was derived from travel surveys for URT passengers in China, was introduced to perform the stochastic network loading at each iteration in the algorithm. Initial tests on the URT network in Shanghai City show that the methodology, with rational calculation time, promises to compute more precisely the passenger flow distribution of URT under network operation, compared with those practical algorithms used in today's China.

Optimization of Telephone Occlusion Method on Urban Rail Transit in Shanghai

Telephone occlusion method is a backup manual occlusion method during an urban rail transit signal equipment failure, which ensures that metro operated safely and orderly. Through the results of several telephone occlusion exercises, find out the shortcomings oftclcphone occlusion method and optimizing it.

Study on the Evaluation of the New Line of Urban Rail Transit Based on Analytic Hierarchy Process

The basic conditions of Urban rail transit line test operation are mainly based on Basic condition for trial operation of urban rail transit （GB/T30013-2013） the basic conditions of the relevant provisions, but the status and standard of trial operation of the basic conditions for assessment of the operating departments are still inadequate, during the three mouth of trial running operations, the specific work of trial operation and exercise are not clear about what this study focuses. This study emphasizes on the methods of operation assessment, through the Analysis Hierarchy Process （AHP） to make the commissioning work carry out smoothly and effectively, making the running exercise Rally, and the emergency and safety follow-up operation process can be quickly handled properly, and it is also helpful to the sustainable development of urban raft transit.

Coupling analysis of passenger and train flows for a large-scale urban rail transit system

Coupling analysis of passenger and train flows is an important approach in evaluating and optimizing the operation efficiency of large-scale urban rail transit(URT)systems.This study proposes a passenger–train interaction simulation approach to determine the coupling relationship between passenger and train flows.On the bases of time-varying origin–destination demand,train timetable,and network topology,the proposed approach can restore passenger behaviors in URT systems.Upstream priority,queuing process with first-in-first-serve principle,and capacity constraints are considered in the proposed simulation mechanism.This approach can also obtain each passenger’s complete travel chain,which can be used to analyze(including but not limited to)various indicators discussed in this research to effectively support train schedule optimization and capacity evaluation for urban rail managers.Lastly,the proposed model and its potential application are demonstrated via numerical experiments using real-world data from the Beijing URT system(i.e.,rail network with the world’s highest passenger ridership).

Last train timetable optimization for metro network to maximize the passenger accessibility over the end-of-service period

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.

Preliminary Study on Selling Tickets in Reason for Last Trains on Beijing Rail Transit Network

With the increase of Beijing urban rail transport network, the structure of the road network is becoming more complex, and passengers have more travel options. Together with the complex paths and different timetables, taking the last train is becoming much more difficult and unsuccessful. To avoid losses, we propose feasible suggestions to the last train with reasonable selling tickets system.

Hourly energy consumption characteristics of metro rail transit:Train traction versus station operation

The electricity consumption of the urban metro system can be mainly divided into the following two categories:the electricity consumption for train traction(E_(t))and the electricity consumption for station operation(E_(s)).Although understanding the hourly fluctuation characteristics of E_(t) and E_(s) contributes to renewable energy inte-gration and achieving carbon emission reduction of the metro system,the hourly fluctuation characteristics have been poorly reported in the literature.Thus,a typical underground non-transfer metro station of a city’s metro system in the North China Plain is selected in this study,and E_(t) and E_(s) were monitored to portray their hourly fluctuation characteristics.Results reveal that the hourly E_(t) shows a significant intraday“U”shape on weekdays,indicating two symmetric peaks in morning and evening rush hours.While the hourly E_(s) shows an intraday“flat”shape,indicating it is nearly free from the effect of rush hour.Moreover,it is statistically proved that the train frequency is the core influencing factor resulting in the intraday fluctuation of hourly E_(t).In the case study,when the train frequency increases from the mean(20 trains per hour)to maximum(32 trains per hour),the hourly E_(t) will increase by 53.4%.

Urban rail transit disruption management: Research progress and future directions

Urban rail transit (URT) disruptions present considerable challenges due to several factors: i) a high probability of occurrence, arising from facility failures, disasters, and vandalism;ii) substantial negative effects, notably the delay of numerous passengers;iii) an escalating frequency, attributable to the gradual aging of facilities;and iv) severe penalties, including substantial fines for abnormal operation. This article systematically reviews URT disruption management literature from the past decade, categorizing it into pre-disruption and post-disruption measures. The pre-disruption research focuses on reducing the effects of disruptions through network analysis, passenger behavior analysis, resource allocation for protection and backup, and enhancing system resilience. Conversely, post-disruption research concentrates on restoring normal operations through train rescheduling and bus bridging services. The review reveals that while post-disruption strategies are thoroughly explored, pre-disruption research is predominantly analytical, with a scarcity of practical pre-emptive solutions. Moreover, future research should focus more on increasing the interchangeability of transport modes, reinforcing redundancy relationships between URT lines, and innovating post-disruption strategies.

Research on Multi-Objective Real-Time Optimization of Automatic Train Operation(ATO) in Urban Rail Transit

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.

Urban rail departure capacity analysis based on a cellular automaton model

As an important traffic mode, urban rail transit is constantly developing toward improvement in service capacity and quality. When an urban rail transit system is evaluated in terms of its service capacity, the train departure capacity is an important index that can objectively reflect the service level of an urban rail transit facility. In light of the existing cellular automaton models, this paper proposes a suitable cellular automaton model to analyze the train departure capacity of urban rail transit under different variable factors and conditions. The established model can demonstrate the train operating processes by implementing the proposed sound rules, including the rules of train departure at the origin and intermediate stations, and the velocity and position updating rules. The properties of train traffic are analyzed via numerical experiments. The numerical results show that the departure capacity is negatively affected by the train departure control manner. In addition, （i） the real-time signal control can offer a higher train service frequency; （ii） the departure capacity gradually rises with the decrease in the line design speed to a limited extent; （iii） the departure capacity decreases with extension in the train length; （iv） the number of departed trains decreases as the train stop time increases; （v） the departure capacity is not affected by the section length. However, the longer the length, the worse the service quality of the urban rail transit line. The experiments show that the proposed cellular automaton model can be used to analyze the train service capacity of an urban rail transit system by performing quantitative analysis under various considered factors, conditions, and management modes.

Fault Current Identification of DC Traction Feeder Based on Optimized VMD and Sample Entropy

A current identification method based on optimized variational mode decomposition(VMD)and sample entropy(SampEn)is proposed in order to solve the problem that the main protection of the urban rail transit DC feeder cannot distinguish between train charging current and remote short circuit current.This method uses the principle of energy difference to optimize the optimal mode decomposition number k of VMD;the optimal VMD for DC feeder current is decomposed into the intrinsic modal function(IMF)of different frequency bands.The sample entropy algorithm is used to perform feature extraction of each IMF,and then the eigenvalues of the intrinsic modal function of each frequency band of the current signal can be obtained.The recognition feature vector is input into the support vector machine model based on Bayesian hyperparameter optimization for training.After a large number of experimental data are verified,it is found that the optimal VMD_SampEn algorithm to identify the train charging current and remote short circuit current is more accurate than other algorithms.Thus,the algorithm based on optimized VMD_SampEn has certain engineering application value in the fault current identification of the DC traction feeder.