Assessment Method for Dynamic Impact of Large Passenger Flow on Urban Rail Transit Network: A Case Study on Chengdu East Railway Station

2021 ◽  
pp. 036119812110584
Author(s):  
Ruihua Xu ◽  
Xuyang Song ◽  
Fangsheng Wang ◽  
Feng Zhou
Keyword(s):  
Radionuclide Imaging ◽  
Large Scale ◽  
Clinical Medicine ◽  
Propagation Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Railway Station ◽  
Passenger Flow ◽  
Urban Rail ◽  
The Impact

Large-scale activities, holidays, and emergencies often cause a significantly large burst of passenger flow demand in some urban rail transit (URT) stations in a short time, called large passenger flow (LPF). The LPF will propagate through the entire URT network of the city. The impact of the frequent occurrence of LPF on network service levels is crucial and unpredictable. This article describes an analysis of how this LPF propagates through the entire network inspired by how radionuclide imaging is done in clinical medicine. In this study, with LPF of URT as the research object, a propagation model of LPF in URT based on AFC data, train operation data, and URT network topology data was developed, which was inspired by the concept of radionuclide imaging in clinical medicine. In the condition of obtaining the list of passenger route selection ratios, the dynamic propagation state matrix of the LPF in the network is solved. The contribution value matrix of the LPF was proposed to evaluate the impact of the LPF on the URT network. Considering the LPF in Chengdu East Railway Station, China, as an example, the propagation effect of LPF in the Chengdu Metro network was analyzed, and the effectiveness of the proposed model was confirmed.

scholarly journals Research on Passenger Flow Early Warning of Urban Rail Transit Station Based on System Dynamics

2020 ◽  
Vol 308 ◽  
pp. 01003
Author(s):  
Hui Chen ◽  
Bo Wang ◽  
Wei He ◽  
Jianhu Zheng
Keyword(s):  
System Dynamics ◽  
Early Warning ◽  
Large Scale ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Flows ◽  
Transit Station ◽  
The Impact

Large-scale passenger flows occur frequently during the peak hours of urban rail transit stations and on holidays. Thus, the timely and accurate early warning of impending large-scale passenger flows can positively impact the operational safety of the entire station. By further deepening the definition of passenger flow warnings in stations, a new model of urban rail transit station passenger flow based on system dynamics is constructed. The method of determining the key area of passenger flows in the early warning stage based on streamlines is proposed; the key indicators and thresholds affecting early warnings are studied. Finally, taking a typical station as an example, a station model is built using Anylogic software. The parameter sensitivity analysis is used to determine the impact of each key indicator on the passenger flow in the key area of the station early warning, and the reference threshold of each indicator is determined.

Research on the Common Rail Transport System Building in Integration System of Urban Rail Transit in Hohhot

2014 ◽  
Vol 599-601 ◽  
pp. 599-602 ◽  
Author(s):  
Cheng Bing Li ◽  
Yi Zhang ◽  
Rui Xue Guo
Keyword(s):  
Product Design ◽  
Transport System ◽  
Rail Transport ◽  
Urban Rail Transit ◽  
Common Rail ◽  
Rail Transit ◽  
Characteristic Analysis ◽  
Passenger Flow ◽  
Urban Rail ◽  
The Impact

Based on the impact analysis of common rail transportation on urban rail transit and comprehensive consideration of Hohhot, including passenger flow characteristic analysis and related product design principle, this paper studies the impact of common rail transport system on the urban rail transit and describes the product design of common rail transport system of Hohhot in two aspects: common rail train stop plan and the nature of the passenger flow, which is dedicated to provide relevant theoretical basis for the rail transit planning and construction of Hohhot in the future. Key words: the integration of urban rail transit; common rail transport; product design; Hohhot

scholarly journals The Effects of Weather on Passenger Flow of Urban Rail Transit

2020 ◽  
Vol 6 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Xiaoyuan Wang ◽  
Yongqing Guo ◽  
Chenglin Bai ◽  
Shanliang Liu ◽  
Shijie Liu ◽  
...  
Keyword(s):  
Urban Rail Transit ◽  
Rail Transit ◽  
Linear Regression Method ◽  
Effective Strategies ◽  
Passenger Flow ◽  
Transit Ridership ◽  
Urban Rail ◽  
Research Findings ◽  
Increasing Temperature ◽  
The Impact

Predicting passenger flow on urban rail transit is important for the planning, design and decision-making of rail transit. Weather is an important factor that affects the passenger flow of rail transit by changing the travel mode choice of urban residents. This study aims to explore the influence of weather on urban rail transit ridership, taking four cities in China as examples, Beijing, Shanghai, Guangzhou and Chengdu. To determine the weather effect on daily ridership rate, the three models were proposed with different combinations of the factors of temperature and weather type, using linear regression method.   The large quantities of data were applied to validate the developed models.  The results show that in Guangzhou, the daily ridership rate of rail transit increases with increasing temperature. In Chengdu, the ridership rate increases in rainy days compared to sunny days. While, in Beijing and Shanghai, the ridership rate increases in light rainfall and heavy rainfall (except moderate rainfall) compared to sunny days. The research findings are important to understand the impact of weather on passenger flow of urban rail transit. The findings can provide effective strategies to rail transit operators to deal with the fluctuation in daily passenger flow.

Research on Hyperpaths in the Urban Rail Transit Network

2014 ◽  
Vol 488-489 ◽  
pp. 1439-1443
Author(s):  
Jin Hai Li ◽  
Jian Feng Liu
Keyword(s):  
Large Scale ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Network ◽  
Travel Costs ◽  
Urban Rail ◽  
Distinctive Structure ◽  
Feasible Path ◽  
Definition Of ◽  
Urban Rail Transit Network

Hyperpaths enumeration is one of the basic procedures in many traffic planning issues. As a result of its distinctive structure, hyperpaths in Urban Rail Transit Network (URTN) are different from those in road network. Typically, one may never visit a station more than once and would never transfer from one line to another that has been visited in a loopless URTN, meaning that stations a hyperpath traversed cannot be repeated, neither do lines in loopless networks. This paper studies the relationships between feasible path and the shortest path in terms of travel costs. In this paper, a new definition of hyperpath in URTN is proposed and a new algorithm based on the breadth first searching (BFS) method is presented to enumerate the hyperpaths. The algorithm can safely avoid hyperpath omission and can even be applied in networks containing loops as well. The influence of parameters on hyperpaths is studied by experimentally finding hyperpaths in the subway network in Beijing. A group of suggested parameter pairs are then given. Finally, a numerical experiment is used to illustrate the validity of the proposed algorithm. The results imply the significance of the convergence of the BFS algorithm which can be used to search hyperpaths in large scale URTN even with loop.

Passenger Flow Forecast of Urban Rail Transit Based on Support Vector Regression

2013 ◽  
Vol 433-435 ◽  
pp. 612-616 ◽  
Author(s):  
Bin Xia ◽  
Fan Yu Kong ◽  
Song Yuan Xie
Keyword(s):  
Support Vector Regression ◽  
Risk Function ◽  
Urban Rail Transit ◽  
Support Vector ◽  
Rail Transit ◽  
Risk Minimization ◽  
Promising Alternative ◽  
Minimization Principle ◽  
Passenger Flow ◽  
Urban Rail

This study analyses and compares several forecast methods of urban rail transit passenger flow, and indicates the necessity of forecasting short-term passenger flow. Support vector regression is a promising method for the forecast of passenger flow because it uses a risk function consisting of the empirical error and a regularized term which is based on the structural risk minimization principle. In this paper, the prediction model of urban rail transit passenger flow is constructed. Through the comparison with BP neural networks forecast methods, the experimental results show that applying this method in URT passenger flow forecasting is feasible and it provides a promising alternative to passenger flow prediction.

Operation Organization at Urban Rail Transit Station under Large Passenger Flow

2012 ◽  
Vol 253-255 ◽  
pp. 1995-2000
Author(s):  
Qiao Mei Tang ◽  
Li Ping Shen ◽  
Xian Yong Tang
Keyword(s):  
Transport Process ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Common Condition ◽  
Urban Transit ◽  
Passenger Flow ◽  
Operation Process ◽  
Urban Rail ◽  
Transit Station ◽  
Transit Operation

large passenger flow is a common condition of urban transit operation, and the station bears the pressure of large passenger flow directly. This paper analyzes the reason for the appearance of large passenger flow and the characteristics of it, discusses the principles and methods that the station can apply under large passenger flow combined with the passenger’s transport process and the operation process.

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