Urban Rail Transit Network Research Articles

Scheduling synchronization in urban rail transit networks: Trade-offs between transfer passenger and last train operation

The scheduling synchronization problem in this paper is to obtain an optimal schedule by optimizing running time, departure time, dwell time and arrival time of the last train in urban rail transit networks. Operators are often faced with multiple conflicting requirements simultaneously such as high passenger’s service quality and less cost, smooth transfer events and less passenger’s travel time, and high accessibility and less operation time. Thus, researchers in this industry concentrate on utilizing operations and management decisions to solve the scheduling problem while balancing the service trade-offs. In this paper, we formulate a mixed integer programming approach for the last train schedule planning, and passengers benefit from smoother transfer in the form of maximizing the transfer synchronization events, while operators simultaneously can benefit with lower operation costs by minimizing the worst big difference between last trains. We propose an improved non-dominated sorting approach embedded in a genetic algorithm to obtain close-to-optimal solutions in a much shorter time for a sophisticated, real-world and large-scale Beijing subway network. Results demonstrate that significant service performance gains (76.33% for Just-missed, 32.01% for successful transfer, 15.39% for non-equity for last trains and 45.25% for variance indicators, etc.), which indicate the effectiveness of the proposed modeling framework and solution algorithm. The operator formulates an efficient schedule for the actual operation of the urban rail transit network by the proposed application method, and it also would be applicable to solving schedule problems among a large-scale network in other industries.

Safety evaluation system of urban traffic network based on topological genetic algorithm

With the rapid development of rail transit, it puts forward higher requirements for safety. Once a safety accident occurs, it is highly destructive. It is of crucial significance and value to ensuring the safety of urban rail transit network by const

Discovering the evolution of Beijing Rail Network in fifty years

Urban rail transit (URT) system plays a significant role in daily commuting. The main features of URT could be abstracted into two kinds of networks, topological network and transit network. The correlation between topological network and transit network could represent the service level of transportation which is also a main focus to some extent. In this study, static analysis based on one year or single analysis based on one aspect are abundant, the main reason of which is the deficiency of the consistent demand data. In this regard, a comprehensive analysis of the evolution and their correlation of the two network are carried out in this work. We first revisit the topological evolution of rail network on the basis of URT network statistic indicators with a fifty-year time span. Then, based on the traditional node-place model, a correctional node-place model between demand spatial distribution and closeness centrality is established. Pearson correlation coefficient is also employed for a precise analysis. Finally, the application of the model and the corresponding analysis on Beijing Subway System (BSS) examine and evaluate the development level and service level of URT system in Beijing, and some solid evidence for relative decision-making is provided.

Risk analysis of Chongqing urban rail transit network

Urban rail network safety is a critical sector of urban public safety. However, there is no uniform standard for the safety evaluation of the urban rail network. This paper presents a novel methodology by integrating a multilevel decision tree with a fuzzy analytical approach to enhance urban rail network safety. The proposed methodology overcomes serious limitations such as subjectivity in the data and independence of the variables in decision-making processes. The proposed methodology is applied to the risk evaluation of the selected Chongqing rail transit lines and the Expo Line. The risk analysis is considered using the field data collected from these transit lines. The applied case studies confirm the general applicability of the methodology and the multilevel decision tree network. The main risk factors identified for the Chongqing rail traffic system are the terrorist threat, emergency management, and aging infrastructure which need to be investigated as a priority to mitigate risk associated with these infrastructures.

First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction

This paper proposes a novel model to optimize the first train timetables for urban rail transit networks, with the goal of maximizing passengers’ transfer waiting time satisfaction. To build up the relationship of transfer waiting time and passenger satisfaction, a reference-based piecewise function is formulated with the consideration of passengers’ expectations, tolerances and dissatisfaction on “just miss”. In order to determine the parameters of zero waiting satisfaction rating, the most comfortable waiting time, and the maximum tolerable waiting time in time satisfaction function, a stated preference survey is conducted in rail transit transfer stations in Shanghai. An artificial bee colony algorithm is developed to solve the timetabling model. Through a real-world case study on Shanghai’s urban rail transit network and comparison with the results of minimizing the total transfer time, we demonstrate that our approach performs better in decreasing extremely long wait and “just miss” events and increasing the number of passengers with a relatively comfortable waiting time in [31s, 5min). Finally, four practical suggestions are proposed for urban rail transit network operations.

Service replanning in urban rail transit networks: Cross-line express trains for reducing the number of passenger transfers and travel time

Reducing the number of transfers and improving the operating speed are key factors in enhancing the competitiveness of urban rail transit (URT) systems. This paper proposes an integrated optimization with tactical cross-line planning and an operational express train mode to fully utilize line capacities and reduce the total trip time without additional operating costs and investments. In this paper, a new mixed integer non-linear programming (MINLP) model is proposed for systemically exploring the benefits of cross-line express trains to achieve both passenger travel time and operation cost savings; in this model, the frequencies, stopping patterns and operation zones of cross-line express trains and local trains are simultaneously optimized. The characteristics of same-line trips (SLT) and cross-line trips (CLT) under various stopping patterns are investigated. Additionally, a genetic algorithm (GA) is developed based on the MINLP model. Finally, the effectiveness of the proposed model and heuristic algorithm is verified through a set of real-life instances based on the Beijing URT network. The results show that the number of transfers can be reduced by 78%, with a 3.34% savings of travel time and a 4.66% savings of operating costs, when the cross-line express operating mode is properly adjusted.

Measures of Travel Reliability on an Urban Rail Transit Network

AbstractTo evaluate the travel reliability of an urban rail transit (URT) in normal operation, three travel reliability indicators are proposed from passengers’ travel. The connectivity reliability...

Evaluating the Relation Between Station Area Design Parameters and Transit Usage for Urban Rail Systems in Ankara, Turkey

Urban rail transit (URT) systems are particularly favoured by planners due to their potential in attracting car users. However, a URT investment must be complemented by land-use characteristics at macroscale (whole city) and design parameters at microscale (vicinity of the station). Despite the common referencing to key concepts (i.e. density, diversity and connectivity), the variability in their definitions and scales causes ambiguity in the determination of their quantified impact on URT ridership. Furthermore, their impact may be different in developing countries, where more mesoscale (corridor-based) effects are expected in the early stages of the URT network. This study aimed to evaluate mathematically the impact of eight selected station design and public transit supply variables on ridership, based on data collected at 14 stations of two existing rail system corridors, both metro (M1) and light rail transit (A1) lines in Ankara, Turkey. Principal component analysis (PCA) indicated three major groups of parameters: (1) land use, (2) public transit supply and (3) connectivity around stations. In single-variable regression models, density and diversity were not found to be statistically significant factors despite the commonly accepted conceptual relation to ridership. A multiple regression model with bus frequency and density (R2 = 0.902) explained the ridership in Ankara URT systems more significantly at its early development stage. There was a significant difference between developed factor relations for both M1 and A1 lines, suggesting that mesolevel impacts should be considered in the evaluation of URT systems.

Collaborative optimization of last-train timetables with accessibility: A space-time network design based approach

To improve the accessibility of the metro network during night operations, this study aims to investigate a collaborative optimization for the last train timetable in an urban rail transit network. By using a space-time network framework, all the involved transportation activities are well characterized in an extended space-time network, in which the train space-time travel arcs, passenger travel arcs, transfer arcs, etc., are all taken into account. Two performance measures are proposed to evaluate the network-based timetable of the last trains. Through considering the route choice behaviors, the problem of interest is formulated as 0–1 linear programming models from the perspective of a space-time network design. To effectively solve the proposed models, we dualize the hard constraints into the objective function to produce the relaxed models by introducing a set of Lagrangian multipliers. Then, the sub-gradient algorithm is proposed to iteratively minimize the gap of the lower and upper bounds of the primal models. Finally, two sets of numerical experiments are implemented in an illustrative network and the Beijing metro network, respectively, and experimental results demonstrate the efficiency and performance of the proposed methods.

A COMPUTATION METHOD ON TIME-DEPENDENT ACCESSIBILITY OF URBAN RAIL TRANSIT NETWORKS FOR THE LAST SERVICE

Urban rail transit networks seldom provide 24-hour service. The last train is the latest chance for passengers. If passengers arrive too late to catch the last train, the path becomes inaccessible. The network accessibility thus varies depending on the departure time of passenger trips. This paper focuses on the computation method on the time-dependent accessibility of urban rail transit networks in order to facilitate the itinerary planning of passengers. A label setting algorithm is first designed to calculate the latest possible times for Origin–Destination (O–D) pairs, which is the latest departure times of passengers from the origins such that the destinations can be reach successfully. A searching approach is then developed to find the shortest accessible path at any possible departure times. The method is applied in a real-world metro network. The results show that the method is a powerful tool in solving the service accessibility problem. It has the ability to allow passengers to plan an optimal itinerary. Comparison analysis indicates that the proposed method can provide exact solutions in much shorter time, compared with a path enumeration method. Extensive tests on a set of random networks indicate that the method is efficient enough in practical applications. The execution time for an O–D pair on a personal computer with 2.8 GHZ CPU and 4GB of RAM is only 1.2 s for urban rail transit networks with 100 transfer stations.

Metro passenger’s path choice model estimation with travel time correlations derived from smart card data

ABSTRACTSmart card data provides a new perspective for estimating a metro passenger’s path choice model in a large-scale urban rail transit network with multiple alternative paths between origin-destination pairs. However, existing research does not consider correlations of path travel times among alternative paths when using smart card data for estimation purposes, leading to biased estimations. This paper proposes an approach to estimating the path choice model considering path travel time correlations. In particular, a simplified form of measuring path travel time correlations caused by shared links is proposed to improve estimation efficiency. Then a framework for a linking path choice model and smart card data is developed based on a Gaussian mixture model; an expectation maximization-based estimation algorithm is also provided. Finally, taking the Guangzhou Metro in China as an example, the superiority of estimations based on smart card data considering correlations is observed in both statistical terms and predictions.

Passenger flow control strategies for urban rail transit networks

Urban rail traffic congestion is becoming increasingly serious due to the large traffic demands in modern cities. In order to ensure the safety and quality of station services in peak hours, it's necessary to adopt some reasonable and effective passenger flow control strategies. In this study, through considering the time-dependent passenger demands, a passenger flow control model based on the network-level system is explicitly developed. The passenger successive motion process is discretized by the modeling method. Systematically considering the coordinated relationship between traffic demands and strict capacity constraints (including station passing capacity, platform load capacity and train transport capacity), we establish a mixed integer linear programming model to minimize the total passenger waiting time (including passengers outside stations and on the platforms). The optimization software Cplex is adopted to solve the developed model, and a real network of Beijing urban railway is calibrated to verify the effectiveness of the suggested model. As a result, the proposed flow control strategies can provide detailed information about control stations, control durations and control intensities, and can effectively reduce the total waiting time and relieve the number of stranded passengers in the urban rail transit network.

Research on the gravity planning model of prefecture city rail transit network

The rational layout of prefecture city rail transit network is of great significance to the coordinated development of urban and rural areas. This paper analyses five related factors that affect the layout of rail transit and grey relation analysis is used to analyse the correlation degree and weight of five related factors. Based on this, an improved gravity model describing the attraction between towns is built. The improved gravity model is used as the road weight, and the urban rail transit network layout is obtained by graph theory Kruskal algorithm. Finally, taking the urban rail transit network in Handan as an example, the rationality and feasibility of the model and layout method are checked.

Classifications of Stations in Urban Rail Transit based on the Two-step Cluster

Different types of stations have different functional roles in the urban rail transit network. Firstly, based on the characteristics of the urban rail transit network structure, the time series features and passenger flow features of the station smart card data are extracted. Secondly, we use the principal component analysis method to select the suitable clustering variables. Finally, we propose a station classification model based on the two-step cluster method. The effectiveness of the proposed method is verified in the Beijing subway. The results show that the proposed model can successfully identify the types of urban rail transit stations, clarify the function and orientation of each station.

Research on Energy Efficiency Evaluation of Urban Rail Transit Based on DEA-BCC Model

The scale of urban rail transit network has been expanding in recent years, and the energy consumption of urban rail transit systems is also growing. So the paper intends to study on energy efficiency of urban rail transit so as to help enterprises to reduce energy consumption and operation costs. From the perspective of economics, the paper establishes an evaluation index system for energy efficiency of urban rail transit with multi-inputs and outputs. Then DEA-BCC model is proposed to evaluate the energy efficiency of urban rail transit, and the empirical analysis of Beijing subway Line5, Line15 and Batong Line is carried out to verify its rationality, which aims to find the influencing factors of energy efficiency of urban rail transit from efficiency and slack variable. Last, some suggestions on how to improve energy efficiency of urban rail transit system are given in the paper.

数据驱动的城市轨道交通网络优化策略

数据驱动的城市轨道交通网络优化策略

Connectivity Reliability on an Urban Rail Transit Network from the Perspective of Passenger Travel

Under the background of urbanization and the rapid development of urban rail transit (URT), serious attention has been focused on URT network reliability in recent years. In this work, in order to measure network reliability, three indicators are constructed based on passengers’ tolerable travel paths, passenger travel efficiency and passenger travel realization on a URT network. The passenger tolerability coefficient, which is the ratio of passengers’ tolerable travel time to the shortest possible travel time, is proposed and added to the indicators. It reflects passengers’ behavior with respect to choice of travel paths. The ratio of affected passenger volume (RAPV) is proposed to identify important stations. Finally, the connectivity reliability of Wuhan’s subway network is analyzed by simulating attacks on stations. The results show that the degree centrality, betweenness centrality and RAPV indicators of stations can effectively identify the important stations that have a significant impact on the connectivity reliability of the network. In particular, the RAPV indicator effectively identifies stations that have the greatest influence on passenger travel realization. The connectivity reliability of Wuhan’s subway network is sensitive to passenger tolerability coefficient, and reliability is greater during non-peak hours than during peak hours. In addition, the stations that are important to the connectivity reliability of the Wuhan subway have two features, i.e., they are located at the center of the city, and they are important for connecting subgraphs of the network.

A review on route choice behavior and volume control of passengers in urban rail transit network

The Urban Rail Transit (URT) network possesses the features of multi-route and big volume of passengers. To study the route choice behavior and volume control of passengers is a bridge to match the capacity supply and passenger demand in URT network. It’s also a crucial problem proposed by the networked operation of URT. We analyze systematically the effect factors of passengers’ route choice behavior and related research on passenger volume control in URT network, as well as the updated representation of URT network and nature of passenger demand. Then we set up the integrated calculation formula for general travel cost in URT network. afterwards, we summarize the classical research method for route choice behavior, including its main study procedure, the search and identify method for effective routes, logit model, probability distribution model, multi-agent simulation and calculation of the match probability by using big data e.g. AFC data. Importantly, we propose the framework for joint comprehensive prediction of passenger route choice behavior and volume control in URT network based on big data, which displays the mind map of passenger-flow-based prediction control and intelligent decision for future study. This review has great theoretical and practical meanings in improving the service efficiency and quality of URT, so as to balance the load of each line and station in URT network, as well as to reduce or eliminate the passenger waiting time for those being left behind because of congestion.

Research on Synchronous Network Platform of Rail Transit Signal System Based on Beidou Satellite Navigation

The signal system is an important part of the modern high-volume, high-density rail transit automatic control system, ensuring the safety of trains and passengers, and plays an important role in the high-speed and orderly operation of trains. The paper introduces the latest development and latest requirements of the synchronous network technology of the rail transit communication system; proposes the construction strategy of the urban rail transit network level synchronization network based on the Beidou satellite navigation system; improves the localization rate of the system and realizes the line network level.

Measuring Method of Node Importance of Urban Rail Network Based on H Index

Urban rail stations play an important role in passenger distribution and connectivity intervals in the network. How to effectively and reasonably evaluate their importance in the network is the key to optimizing the urban rail network structure and reducing operational risks. Taking the site as the research object and considering the topology, passenger volume, and passenger flow correlation of the urban rail network, the index of citation index is used to define node importance metric based on the h-index. Furthermore, the method of calculating the importance degree of urban rail transit network nodes based on h-index is proposed. The validity of the method is verified by the data of Beijing urban rail network in 2016, and the results are compared with the existing central index based on the network topology characteristics.