Short-Time Calculation Method of Passenger Flows on Urban Rail Transit Island Platform

2014 ◽  
Vol 644-650 ◽  
pp. 2133-2136
Author(s):  
Tian Shi Li
Keyword(s):  
Probability Theory ◽  
Calculation Method ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Numerical Examples ◽  
Passenger Flow ◽  
Urban Rail ◽  
Time Calculation ◽  
Passenger Flows ◽  
Short Time

Because urban tail transit becomes the preferred way to travel for more travelers, the passenger flow of rail transit is increasing fast. Due to the increased passenger, the congestion on platform reduces the comfort and puts passengers in danger. This article analyses the model of island platform short-time arrivals based on the probability theory and historical statistics. The calculation method is studied and the Feasibility and algorithm is testified by setting numerical examples.

Influence of Emergency Passenger Flow Distribution in Urban Rail Network

2012 ◽  
Vol 450-451 ◽  
pp. 295-301 ◽  
Author(s):  
Ling Hong ◽  
Jia Gao ◽  
Rui Hua Xu
Keyword(s):  
Flow Distribution ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Abstract Model ◽  
Flow Volume ◽  
Rail Network ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Flows ◽  
Urban Rail Transit Network

The emergency disposal of urban rail transit needs to accurately estimate the emergency range and total affected passenger flow volume. The urban rail transit network could be simplified to an abstract model which is easy to be analyst based on the graph theory method. Considering the actual network back-turning lines and vehicle storage tracks of urban rail network, the emergency range could be estimated effectively. The affected passenger flow could be classified as different kinds based on the different paths of passenger flow. The classification of passenger flow mainly includes “delay passenger flow”, “detour passenger flow” and “loss passenger flow”. Considering the emergency range, the different affected passenger flows could be superposed over time based on the abstract model, then the affected passenger flow volume and virtual loss time could be calculated out. The results could provide basis for the emergency disposal in urban rail transit. The example analysis is verified the feasibility of this method.

scholarly journals Urban Rail Transit System Network Reliability Analysis Based on a Coupled Map Lattice Model

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Shaojie Wu ◽  
Yan Zhu ◽  
Ning Li ◽  
Yizeng Wang ◽  
Xingju Wang ◽  
...  
Keyword(s):  
Complex Network ◽  
Network Reliability ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Weighted Network ◽  
Network Nodes ◽  
Transit Network ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Flows

During the last twenty years, the complex network modeling approach has been introduced to assess the reliability of rail transit networks, in which the dynamic performance involving passenger flows have attracted more attentions during operation stages recently. This paper proposes the passenger-flow-weighted network reliability evaluation indexes, to assess the impact of passenger flows on network reliability. The reliability performances of the rail transit network and passenger-flow-weighted one are analyzed from the perspective of a complex network. The actual passenger flow weight of urban transit network nodes was obtained from the Shanghai Metro public transportation card data, which were used to assess the reliability of the passenger-flow-weighted network. Furthermore, the dynamic model of the Shanghai urban rail transit network was constructed based on the coupled map lattice (CML) model. Then, the processes of cascading failure caused by network nodes under different destructive situations were simulated, to measure the changes of passenger-flow-weighted network reliability during the processes. The results indicate that when the scale of network damage attains 50%, the reliability of the passenger-flow-weighted network approaches zero. Consequently, taking countermeasures during the initial stage of network cascading may effectively prevent the disturbances from spreading in the network. The results of the paper could provide guidelines for operation management, as well as identify the unreliable stations within passenger-flow-weighted networks.

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.

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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