scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

scholarly journals A Timetable Optimization Model for Urban Rail Transit with Express/Local Mode

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Renjie Zhang ◽  
Shisong Yin ◽  
Mao Ye ◽  
Zhiqiang Yang ◽  
Shanglu He
Keyword(s):  
Waiting Time ◽  
Optimization Model ◽  
Urban Rail Transit ◽  
Local Mode ◽  
Rail Transit ◽  
Long Distance ◽  
Urban Rail ◽  
Proposed Model ◽  
Distance Travel ◽  
Timetable Optimization

Nowadays, an express/local mode has be studied and applied in the operation of urban rail transit, and it has been proved to be beneficial for the long-distance travel. The optimization of train patterns and timetables is vital in the application of the express/local mode. The former one has been widely discussed in the various existing works, while the study on the timetable optimization is limited. In this study, a timetable optimization model is proposed by minimizing the total passenger waiting time at platforms. Further, a genetic algorithm is used to solve the minimization problems in the model. This study uses the data collected from Guangzhou Metro Line 14 and finds that the total passenger waiting time at platforms is reduced by 9.3%. The results indicate that the proposed model can reduce the passenger waiting time and improve passenger service compared with the traditional timetable.

scholarly journals Data-Driven Approaches to Mining Passenger Travel Patterns: “Left-Behinds” in a Congested Urban Rail Transit Network

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Xing Chen ◽  
Leishan Zhou ◽  
Zixi Bai ◽  
Yixiang Yue ◽  
Bin Guo ◽  
...  
Keyword(s):  
Travel Demand ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Travel Patterns ◽  
Train Control ◽  
Left Behind ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Time Parameters

The “left-behind” phenomenon occurs frequently in Urban Rail Transit (URT) networks with booming travel demand, especially during peak hours in a complex URT network, which makes passenger travel patterns more complicated. This paper proposes a methodology to mine passenger travel patterns based on fare transaction records from automatic fare collection (AFC) systems and Automatic Vehicle Location (AVL) data from Communication Based Train Control (CBTC) Systems or tracking systems. By introducing the concept of a sequence, a space-time-sequence trajectory model is proposed to simulate a passenger’s travel activities, including when they are left-behind. The paper analyzes passenger travel trajectory links and estimates the weight of each feasible trajectory under tap-in/tap-out constraints. The station time parameters, including access/egress and transfer walking-time parameters, are important inputs for the model. The paper also presents a maximum-likelihood approach to estimate these parameters from AFC transaction data and AVL data. The methodology is applied to a case study using AFC and AVL data from the Beijing URT network during peak hours to test the proposed model and algorithm. The estimation results are consistent with the results obtained from the authorities, and this finding verifies the feasibility of our approach.

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

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.

Can urban rail transit curb automobile energy consumption?

Energy Policy ◽  
2017 ◽  
Vol 105 ◽  
pp. 120-127 ◽  
Author(s):  
Boqiang Lin ◽  
Zhili Du
Keyword(s):  
Energy Consumption ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Urban Rail

Thinking of Comprehensive Energy-Saving System Construction for Urban Rail Transit

2014 ◽  
Vol 505-506 ◽  
pp. 405-409
Author(s):  
Jun Ke Liang ◽  
Zhi Gang Liu ◽  
Yuan Chun Huang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Optimization Design ◽  
High Efficiency ◽  
High Energy ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
System Construction ◽  
Planning Period ◽  
Urban Rail

The High Energy Consumption of the Current Urban Rail Transit Industry, High Efficiency Energy Saving Measures must be Taken. this Paper Entity from the Traction Energy Consumption, Building Structure and Operating Equipment Aspects of the Current Situation, Described the Energy Saving Strategies. Aiming at the Present Problems Existing in Energy Saving Practice, this Article Puts Forward the Comprehensive Energy Saving System which Contains Optimization Design in Planning Period, Low Resource Consumption in Construction Period, Energy Saving Work in Operation Period. above all, Implement Energy Saving Practice at Every Concrete Work of Reaching.

Study of the Influencing Factors of Urban Rail Transit Travel Behavior: A Case Study of Xi'an

2015 ◽  
Vol 744-746 ◽  
pp. 2049-2052
Author(s):  
Yao Wu ◽  
Jian Lu ◽  
Yue Chen
Keyword(s):  
Travel Time ◽  
Influencing Factors ◽  
Travel Behavior ◽  
Family Income ◽  
Binary Logistic Regression ◽  
Travel Distance ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Binary Logistic Regression Model ◽  
Urban Rail

In order to study the factors influencing urban rail transit travel behavior, a questionnaire was conducted for residents’ selection of rail transit in Xi'an. Based on the collected data from 1105 valid questionnaires, a binary logistic regression model was established to analyze the influencing factors quantitatively. The results showed that seven factors have statistically significant for rail transit travel behavior including age, occupation, family income, average monthly household transportation costs (T-cost), travel purpose, travel distance, and travel time. Odds ratio analysis revealed that young people and staff were more likely to choose rail transit; the probability of selecting rail transit increased with the increase of family income and the T-cost. In addition, more and more people tend to rail travel with the increase of travel distance and travel time.

The Optimization of Arriving and Departing Time of Trains in Urban Rail Transit Based on Passenger Transfer

2014 ◽  
Vol 587-589 ◽  
pp. 1958-1962
Author(s):  
Jie Ping Sun
Keyword(s):  
Travel Time ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Operation Process ◽  
Urban Rail ◽  
Practical Operation ◽  
Time Extension ◽  
Transfer Stations ◽  
Important Significance ◽  
Beijing Subway

In this paper, there is a study on the effect of the lack of coordination between trains in the network, such as waiting aggravation, travel time extension. Through the study of the practical operation process and passenger transfer characteristics of urban rail transit, according to the types of line crossing, taking the minimized waiting time of all transfer passengers in station as the object function, the optimization model was designed for three lines with two intersections, solve the model by using the Lingo, and transfer stations, Xidan and Dongdan station, from lines No.1 No.4 and No.5 of Beijing Subway Network are chosen as an example to validate its rationality and availability. The result shows that the model is of important significance to reduce the travel time for transfer passengers.

Scenario-Based Integrated Assignment Model for Bi-Class User Rail Transit Networks

2013 ◽  
Vol 361-363 ◽  
pp. 1963-1966
Author(s):  
Wei Zhu
Keyword(s):  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Networks ◽  
Assignment Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Scale Network ◽  
Algorithm Framework ◽  
Real Scale

An integrated assignment model for urban rail transit (URT) networks was proposed and discussed in four typical scenarios with the consideration of passenger difference between native and non-native. An overall algorithm framework for the model was also developed, which introduced three critical route choice models and combined them appropriately to different scenarios. A case study was performed on a real-scale network of Shanghai during the Expo 2010. The results revealed that the proposed model can deliver more appropriate solution to the assignment problem compared to the existing practice in the real world.

Sign in / Sign up

Export Citation Format

Share Document