A Short Turning Strategy for Train Scheduling Optimization in an Urban Rail Transit Line: The Case of Beijing Subway Line 4

In urban rail transit systems, train scheduling plays an important role in improving the transport capacity to alleviate the urban traffic pressure of huge passenger demand and reducing the operation costs for operators. This paper considers the train scheduling with short turning strategy for an urban rail transit line with multiple depots. In addition, the utilization of trains is also taken into consideration. First, we develop a mixed integer nonlinear programming (MINLP) model for the train scheduling, where short turning train services and full-length train services are optimized based on the predefined headway obtained by the passenger demand analysis. The MINLP model is then transformed into a mixed integer linear programming (MILP) model according to several transformation properties. The resulting MILP problem can be solved efficiently by existing solvers, e.g., CPLEX. Two case studies with different scales are constructed to assess the performance of train schedules with the short turning strategy based on the data of Beijing Subway line 4. The simulation results show that the reduction of the utilization of trains is about 20.69%.

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Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji

Energies ◽

10.3390/en13040782 ◽

2020 ◽

Vol 13 (4) ◽

pp. 782

Author(s):

Na Zhang ◽

Zijia Wang ◽

Feng Chen ◽

Jingni Song ◽

Jianpo Wang ◽

...

Keyword(s):

Carbon Emissions ◽

Quantitative Research ◽

Carbon Emission ◽

Urban Traffic ◽

Urban Rail Transit ◽

Rail Transit ◽

Low Carbon ◽

Demand Forecast ◽

Passenger Demand ◽

Urban Rail

There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation types is changing along with the adjustment of the urban traffic structure and a growing demand from passengers. The reduction of carbon emissions brought about by rail transit lacks specific quantitative research. Based on a travel survey of urban residents, this paper constructed a method of estimating carbon emissions from two different scenarios where rail transit is and is not available. This study uses the traditional four-stage model to forecast passenger volume demand at the city level and then obtains the basic target parameters for constructing the carbon emission reduction model, including the trip origin-destination (OD), mode, and corresponding distance range of different modes on the urban road network. This model was applied to Baoji, China, where urban rail transit will be available from 2023. It calculates the changes in carbon emission that rail transit can bring about and its impact on carbon emission reductions in Baoji in 2023.

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Optimal Operation Scheme with Short-Turn, Express, and Local Services in an Urban Rail Transit Line

Journal of Advanced Transportation ◽

10.1155/2020/5830593 ◽

2020 ◽

Vol 2020 ◽

pp. 1-19

Author(s):

Tao Feng ◽

Siyu Tao ◽

Zhengyang Li

Keyword(s):

Search Algorithm ◽

Real Life ◽

Optimal Operation ◽

Urban Rail Transit ◽

Mixed Integer ◽

Rail Transit ◽

Nonlinear Program ◽

Urban Rail ◽

Local Services ◽

Minlp Model

Flexible railway operation modes combining different operation strategies, such as short-turn, express, and local services, can significantly reduce operator and user costs and increase the efficiency and attractiveness of rail transit services. It is therefore necessary to develop optimization models to find optimal combinations of operation strategies for urban rail transit lines. In this paper, a model is proposed for solving the urban rail transit operation scheme problem. The model considers short-turn, express, and local services with the aim of minimizing the operator’s and users’ costs. The problem is first decomposed into two subproblems: the service route design problem and the passenger assignment problem. Then, a mixed-integer nonlinear program (MINLP) model is formulated, and linearization techniques are utilized to transform the MINLP model into a mixed-integer linear programming (MILP) model that can be easily solved by commercial optimization solvers. To accelerate the solution process, a heuristic search algorithm is proposed to obtain (nearly) optimal solutions based on the characteristics of the model. The two subproblems are solved iteratively to improve the quality of solutions. A real-life case study in Chengdu, China, is performed to demonstrate the effectiveness and efficiency of the proposed model and algorithm.

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A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

Journal of Advanced Transportation ◽

10.1155/2020/3809734 ◽

2020 ◽

Vol 2020 ◽

pp. 1-18 ◽

Cited By ~ 1

Author(s):

Qingwei Zhong ◽

Yongxiang Zhang ◽

Dian Wang ◽

Qinglun Zhong ◽

Chao Wen ◽

...

Keyword(s):

Linear Programming ◽

Integer Linear Programming ◽

Mixed Integer Linear Programming ◽

Urban Rail Transit ◽

Mixed Integer ◽

Rolling Stock ◽

Rail Transit ◽

Urban Rail ◽

Operation Period ◽

Train Services

In an urban rail transit line, train services are performed by the rolling stocks that are initially stored at depots. Before the start of the operation period, rolling stocks consecutively leave the depots and run without passengers (deadhead routing) to the origin station of their corresponding first departure train service in an operation day (first train service) using either direct or indirect routes. This paper investigates the rolling stock deadhead routing problem in an urban transit line with multiple circulation plans, depots, and rolling stock types. Given the rolling stock circulation plans, the problem is to identify a deadhead route for the rolling stock required by the train services to cover the initial operation. By pregenerating all direct and indirect candidate deadhead routes in a polynomial manner, the problem is then nicely formulated as a mixed integer linear programming (MILP) model to minimize the total deadhead mileages. A real-world case from the urban rail transit line 3 of Chongqing in China is adopted to test the proposed method. Computational results demonstrate that the problems of large-scale instances can be quickly solved to optimality by commercial optimization solvers on a personal computer. In addition, our optimization method is better than the empirical practices in terms of the solution quality. Meanwhile, alternative measures can further decrease the total deadhead mileages according to the proposed model, e.g., opening idle switch stations and prolonging the time that is used for the rolling stock departure. Finally, the model is further extended to consider operating costs, and more computation cases are tested for better adapting to the practical operating conditions.

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Passenger demand oriented train scheduling and rolling stock circulation planning for an urban rail transit line

Transportation Research Part B Methodological ◽

10.1016/j.trb.2018.10.006 ◽

2018 ◽

Vol 118 ◽

pp. 193-227 ◽

Cited By ~ 26

Author(s):

Yihui Wang ◽

Andrea D’Ariano ◽

Jiateng Yin ◽

Lingyun Meng ◽

Tao Tang ◽

...

Keyword(s):

Urban Rail Transit ◽

Rolling Stock ◽

Rail Transit ◽

Train Scheduling ◽

Passenger Demand ◽

Urban Rail

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Multiperiod Transfer Synchronization for Cross-Platform Transfer in an Urban Rail Transit System

Symmetry ◽

10.3390/sym12101665 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1665

Author(s):

Nan Cao ◽

Tao Tang ◽

Chunhai Gao

Keyword(s):

Waiting Time ◽

Transfer Problem ◽

Urban Rail Transit ◽

Mixed Integer ◽

Rail Transit ◽

Multiple Time ◽

Transit System ◽

Passenger Demand ◽

Urban Rail ◽

Cross Platform

Transfer synchronization is an important issue in timetable scheduling for an urban rail transit system, especially a cross-platform transfer. In this paper, we aim to optimize the performance of transfer throughout the daily operation of an urban rail transit system. The daily operation is divided into multiple time periods and each time period has a specific headway to fulfill time varied passenger demand. At the same time, the turn-back process of trains should also be considered for a real operation. Therefore, our work enhances the base of the transfer synchronization model taking into account time-dependent passenger demand and utilization of trains. A mixed integer programming model is developed to obtain an optimal timetable, providing a smooth transfer for cross-transfer platform and minimizing the transfer waiting time for all transfer passengers from different directions with consideration of timetable symmetry. By adjusting the departure time of trains based on a predetermined timetable, this transfer optimization model is solved through a genetic algorithm. The proposed model and algorithm are utilized for a real transfer problem in Beijing and the results demonstrate a significant reduction in transfer waiting time.

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An integrated approach of train scheduling and rolling stock circulation with skip-stopping pattern for urban rail transit lines

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2021.103170 ◽

2021 ◽

Vol 128 ◽

pp. 103170

Author(s):

Shuo Zhao ◽

Hai Yang ◽

Yinghui Wu

Keyword(s):

Integrated Approach ◽

Urban Rail Transit ◽

Rolling Stock ◽

Rail Transit ◽

Train Scheduling ◽

Urban Rail

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Collaborative passenger flow control of urban rail transit network considering balanced distribution of passengers

Modern Physics Letters B ◽

10.1142/s0217984921504613 ◽

2021 ◽

pp. 2150461

Author(s):

Xiang Li ◽

Yan Bai ◽

Kaixiong Su

Keyword(s):

Flow Control ◽

Programming Model ◽

Flow Characteristics ◽

Service Level ◽

Urban Traffic ◽

Urban Rail Transit ◽

Control Measures ◽

Rail Transit ◽

Passenger Flow ◽

Urban Rail

The increase of urban traffic demands has directly affected some large cities that are now dealing with more serious urban rail transit congestion. In order to ensure the travel efficiency of passengers and improve the service level of urban rail transit, we proposed a multi-line collaborative passenger flow control model for urban rail transit networks. The model constructed here is based on passenger flow characteristics and congestion propagation rules. Considering the passenger demand constraints, as well as section transport and station capacity constraints, a linear programming model is established with the aim of minimizing total delayed time of passengers and minimizing control intensities at each station. The network constructed by Line 2, Line 6 and Line 8 of the Beijing metro is the study case used in this research to analyze control stations, control durations and control intensities. The results show that the number of delayed passengers is significantly reduced and the average flow control ratio is relatively balanced at each station, which indicates that the model can effectively relieve congestion and provide quantitative references for urban rail transit operators to come up with new and more effective passenger flow control measures.

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