Comprehensive optimization of urban rail transit timetable by minimizing total travel times under time-dependent passenger demand and congested conditions

2018 ◽  
Vol 58 ◽  
pp. 421-446 ◽  
Author(s):  
Tianyu Zhang ◽  
Dewei Li ◽  
Yu Qiao
Keyword(s):  
Urban Rail Transit ◽  
Time Dependent ◽  
Rail Transit ◽  
Travel Times ◽  
Passenger Demand ◽  
Urban Rail

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

Energies ◽  
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.

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

Transport ◽  
2020 ◽  
Vol 35 (1) ◽  
pp. 26-36
Author(s):  
Yao Chen ◽  
Baohua Mao ◽  
Yun Bai ◽  
Zhujun Li ◽  
Jimeng Tang
Keyword(s):  
Urban Rail Transit ◽  
Time Dependent ◽  
Computation Method ◽  
Rail Transit ◽  
Practical Applications ◽  
Transit Networks ◽  
Urban Rail ◽  
Accessibility Problem ◽  
Transfer Stations ◽  
Label Setting Algorithm

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.

scholarly journals Urban Rail Transit Scheduling under Time-Varying Passenger Demand

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Xing Zhao ◽  
Zhongyan Hou ◽  
Jihuai Chen ◽  
Yin Zhang ◽  
Junying Sun
Keyword(s):  
Urban Rail Transit ◽  
Load Factor ◽  
Rail Transit ◽  
Time Interval ◽  
Train Timetable ◽  
Passenger Demand ◽  
Scheduling Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Transit Scheduling

In view of the conflict between the time-variation of urban rail transit passenger demand and the homogeneity of the train timetable, this paper takes into account the interests of both passengers and operators to build an urban rail transit scheduling model to acquire an optimized time-dependent train timetable. Based on the dynamic passenger volumes of origin-destination pairs from the automatic fare collection system, the model focuses on minimizing the total passenger waiting time with constraints on time interval between two consecutive trains, number and capacity of trains available, and load factor of trains. A hybrid algorithm which consists of the main algorithm based on genetic algorithm and the nested algorithm based on train traction calculation and safety distance requirement is designed to solve the model. To justify the effectiveness and the practical value of the proposed model and algorithm, a case of Nanjing Metro Line S1 is illustrated in this paper. The result shows that the optimized train timetable has advantage compared to the original one.

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

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Miao Zhang ◽  
Yihui Wang ◽  
Shuai Su ◽  
Tao Tang ◽  
Bin Ning
Keyword(s):  
Urban Traffic ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Rail Transit ◽  
Train Scheduling ◽  
Passenger Demand ◽  
Urban Rail ◽  
Train Services ◽  
Minlp Model ◽  
Beijing Subway

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%.

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

2018 ◽  
Vol 118 ◽  
pp. 193-227 ◽  
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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