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

2013 ◽  
Vol 361-363 ◽  
pp. 1963-1966
Author(s):  
Wei Zhu

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.

2020 ◽  
Vol 12 (14) ◽  
pp. 5756
Author(s):  
Jianhua Zhang ◽  
Ziqi Wang ◽  
Shuliang Wang ◽  
Shengyang Luan ◽  
Wenchao Shao

Urban rail transit has received much attention in the last two decades, and a significant number of cities have established urban rail transit networks (URTNs). Although URTNs have brought enormous convenience to the daily life of citizens, system failures still frequently occur, therefore the vulnerability of URTNs must be a concern. In this paper, we propose a novel measurement called the node strength parameter to assess the importance of nodes and present a redundant recovery scheme to imitate the system recovery of URTNs subjected to failures. Employing three malicious attacks and taking the Nanjing subway network as the case study, we investigated the network vulnerability under scenarios of different simulated attacks. The results illustrate that passenger in-flow shows the negligible impact on the vulnerability of the node, while out-flow plays a considerable role in the largest strength node-based attack. Further, we find that vulnerability will decrease as passenger out-flow increases, and the vulnerability characteristics are the same with the increase in the construction cost of URTNs. Considering different attack scenarios, the results indicate that the highest betweenness node-based attack will cause the most damage to the system, and increasing the construction cost can improve the robustness of URTNs.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Rui-Jia Shi ◽  
Bao-Hua Mao ◽  
Yong Ding ◽  
Yun Bai ◽  
Yao Chen

In an urban rail transit system, it is important to coordinate the timetable of a loop line with its connecting lines so as to reduce the waiting time of passengers. This is particularly essential because transfer passengers usually account for the majority of the total passengers in loop lines. In this paper, a timetable optimization model is developed for loop line in order to minimize the average waiting time of access passengers and transfer passengers. This is performed by adjusting the headways and dwell times of trains on the loop line. A genetic algorithm is applied to solve the proposed model, and a numerical example is used to verify its effectiveness. Finally, a case study of a loop line in the Beijing urban rail transit system is conducted. Waiting times of the passengers and the number of waiting passengers are used as performance indicators to verify the optimization results in rush hours and non-rush hours. The results show that the average waiting times for the up-track and down-track are reduced by 3.69% and 2.89% during rush hours and by 11.60% and 11.47% during non-rush hours, respectively.


2015 ◽  
Vol 7 (6) ◽  
pp. 6919-6936 ◽  
Author(s):  
Daniel Sun ◽  
Yuhan Zhao ◽  
Qing-Chang Lu

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang

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.


2020 ◽  
Vol 12 (10) ◽  
pp. 4166 ◽  
Author(s):  
Xuan Li ◽  
Toshiyuki Yamamoto ◽  
Tao Yan ◽  
Lili Lu ◽  
Xiaofei Ye

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.


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