scholarly journals Optimum Equilibrium Passenger Flow Control Strategies with Delay Penalty Functions under Oversaturated Condition on Urban Rail Transit

2021 ◽  
Vol 2021 ◽  
pp. 1-27
Author(s):  
Yonghao Yin ◽  
Dewei Li ◽  
Kai Zhao ◽  
Ruixia Yang
Keyword(s):  
Flow Control ◽  
Simulated Annealing Algorithm ◽  
Control Strategies ◽  
Penalty Functions ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit System ◽  
Passenger Flow ◽  
Urban Rail ◽  
Linear Delay

When passengers are oversaturated in the urban rail transit system and a further increase of train frequency is impossible, passenger flow control strategy is an indispensable approach to avoid congestion and ensure safety. To make the best use of train capacity and reduce the passenger waiting time, coordinative flow control is necessary at each station on a line. In most published studies, the equilibrium of passenger distributions among different stations and periods is not considered. As a result, two issues occur making it hard to implement in practical. First, a large number of passengers are held up outside a small number of stations for very long time. Second, there is a large variation of controlled flows for successive time intervals. To alleviate this problem, a single-line equilibrium passenger flow control model is constructed, which minimizes the total passenger delay. By applying different forms of the delay penalty function (constant and linear), flow control strategies such as independent flow control and equilibrium flow control can be reproduced. An improved simulated annealing algorithm is proposed to solve the model. A numerical case is studied to analyze the sensitivity of the functions, and the best parameter relationship in different functions could be confirmed. A real-world case from Batong Line corridor in Beijing subway is used to test the applicability of the model and algorithm, and the result shows that the solution with linear delay penalty functions can not only reduce the total passenger delay but also equilibrate the number of flow control passengers on spatial and temporal.

Passenger flow control strategies for urban rail transit networks

2020 ◽  
Vol 82 ◽  
pp. 168-188 ◽  
Author(s):  
Fuya Yuan ◽  
Huijun Sun ◽  
Liujiang Kang ◽  
Jianjun Wu
Keyword(s):  
Flow Control ◽  
Control Strategies ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Networks ◽  
Passenger Flow ◽  
Urban Rail

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.

scholarly journals Understanding the Propagation and Control Strategies of Congestion in Urban Rail Transit Based on Epidemiological Dynamics Model

Information ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 258 ◽  
Author(s):  
Shi ◽  
Zhang ◽  
Lei
Keyword(s):  
Control Strategies ◽  
Urban Rail Transit ◽  
Model Parameters ◽  
Rail Transit ◽  
Dynamics Model ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Volume ◽  
And Control ◽  
Demand Control

With the construction of the urban rail transit (URT) network, the explosion of passenger volume is more rapid than the increased capacity of the newly built infrastructure, which results in serious passenger flow congestion (PLC). Understanding the propagation process of PLC is the key to formulate sustainable policies for reducing congestion and optimizing management. This study proposes a susceptible-infected-recovered (SIR) model based on the theories of epidemiological dynamics and complex network to analyze the PLC propagation. We simulate the PLC propagation under various situations, and analyze the sensitivity of PLC propagation to model parameters. Finally, the control strategies of restricting PLC propagation are introduced from two aspects, namely, supply control and demand control. The results indicate that both of the two control strategies contribute to relieving congestion pressure. The propagating scope of PLC is more sensitive when taking mild supply control, whereas, the demand control strategy shows some advantages in flexibly implementing and dealing with serious congestion. These results are of important guidance for URT agencies to understand the mechanism of PLC propagation and formulate appropriate congestion control strategies.

scholarly journals Fare Optimality Analysis of Urban Rail Transit under Various Objective Functions

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Lianbo Deng ◽  
Zhao Zhang ◽  
Kangni Liu ◽  
Wenliang Zhou ◽  
Junfeng Ma
Keyword(s):  
Simulated Annealing Algorithm ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Elastic Demand ◽  
Benefit Analysis ◽  
Objective Functions ◽  
Passenger Flow ◽  
Urban Rail ◽  
Train Operation ◽  
Annealing Algorithm

Urban rail transit fare strategies include fare structures and fare levels. We propose a rail transit line fare decision based on an operating plan that falls under elastic demand. Combined with the train operation plan, considering flat fare and distance-based fare, and based on the benefit analysis of both passenger flow and operating enterprises, we construct the objective functions and build an optimization model in terms of the operators’ interests, the system’s efficiency, system regulation goals, and the system costs. The solving algorithm based on the simulated annealing algorithm is established. Using as an example the Changsha Metro Line 2, we analyzed the optimized results of different models under the two fare structures system. Finally the recommendations of fare strategies are given.

scholarly journals Passengers Flow Forecasting Model of Urban Rail Transit Based on the Macro-Factors

2012 ◽  
Vol 6-7 ◽  
pp. 688-693 ◽  
Author(s):  
Bin Shang ◽  
Xiao Ning Zhang
Keyword(s):  
Real Data ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Estimation Model ◽  
Population Total ◽  
Transit System ◽  
The Real ◽  
Passenger Flow ◽  
Urban Rail ◽  
Multiple Variables

In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many cities shows that the model is very accurate in passenger flow forecasting.

A cooperative evacuation strategy for mass passenger flow in urban rail transit transfer stations

2020 ◽  
pp. 2150007
Author(s):  
Jia Hong-Fei ◽  
Sang Heng ◽  
Luo Qing-Yu ◽  
Yang Jin-Ling ◽  
Miao Hong-Zhi
Keyword(s):  
Real Life ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Nsga Ii ◽  
Transit System ◽  
Passenger Flow ◽  
Evacuation Strategy ◽  
Urban Rail ◽  
The Status ◽  
Transfer Stations

In reviewing the evacuation problem of mass passenger flow in urban rail transit transfer stations, the cooperative evacuation strategy considering urban rail transit and emergency bus simultaneously is found to be an efficient way. In this work, firstly, the dynamic characteristics of mass passenger flow are analyzed based on the abstraction and simplification of major entities of urban rail transit, including passengers, stations and trains. Then, the operations of the urban rail transit system are modeled, including the boarding, landing and transferring processes of the passengers and the status updating flows of the trains and stations. To realize the cooperative evacuation, a multi-objective optimization model considering the evacuation speed, the number of passengers transferred, and the amount of emergency buses is proposed. The NSGA-II algorithm is adopted to solve the proposed model, which can balance the theoretical validity and computational convenience. Last, the proposed strategy is applied in a real-life case based on the Shanghai Metro line, and the results verify its effectiveness and efficiency.

scholarly journals A Passenger Flow Control Method for Subway Network Based on Network Controllability

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lu Zeng ◽  
Jun Liu ◽  
Yong Qin ◽  
Li Wang ◽  
Jie Yang
Keyword(s):  
Flow Control ◽  
Control Method ◽  
Flow Distribution ◽  
Urban Rail Transit ◽  
Flow Density ◽  
Rail Transit ◽  
System Control ◽  
Flow Network ◽  
Passenger Flow ◽  
Urban Rail

The volume of passenger flow in urban rail transit network operation continues to increase. Effective measures of passenger flow control can greatly alleviate the pressure of transportation and ensure the safe operation of urban rail transit systems. The controllability of an urban rail transit passenger flow network determines the equilibrium state of passenger flow density in time and space. First, a passenger flow network model of urban rail transit and an evaluation index of the alternative set of flow control stations are proposed. Then, the controllable determination model of the urban rail transit passenger flow network is formed by converting the passenger flow distribution into a system state equation based on system control theory. The optimization method of passenger flow control stations is established via driver node matching to realize the optimized control of network stations. Finally, a real-world case study of the Beijing subway network is presented to demonstrate that the passenger flow network is controllable when driver nodes compose 25.3% of the entire network. The optimization of the flow control station, set during the morning peak, proves the efficiency and validity of the proposed model and algorithm.

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