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

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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Passenger-demands-oriented train scheduling for an urban rail transit network

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2015.07.012 ◽

2015 ◽

Vol 60 ◽

pp. 1-23 ◽

Cited By ~ 84

Author(s):

Yihui Wang ◽

Tao Tang ◽

Bin Ning ◽

Ton J.J. van den Boom ◽

Bart De Schutter

Keyword(s):

Urban Rail Transit ◽

Rail Transit ◽

Train Scheduling ◽

Transit Network ◽

Urban Rail ◽

Urban Rail Transit Network

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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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