A Learning Model of Passenger’s Path Choice in Urban Rail Network Based on Bayesian Method

To determine passenger’s path choice is the base for research on ridership distribution in urban rail network. Considering passenger’s multi-days’ trips as a process to continuously update path information expressed by its sample mean and variance of travel cost, the paper establishes a self-learning model of passenger’s path choice in urban rail network based on Bayesian method by analyzing the acquisition of prior information beforetrip and knowledge updating after trip, as well as taking the adjustment of Urban Rail Transit operating conditions into account.The model proposed can be used to analyze the passenger flow formation and evolution mechanism in urban rail network.

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Discovering the evolution of Beijing Rail Network in fifty years

Modern Physics Letters B ◽

10.1142/s0217984920502127 ◽

2020 ◽

Vol 34 (21) ◽

pp. 2050212

Author(s):

Zijia Wang ◽

Jingqi Li ◽

Liping Huang ◽

Zhigang Yang

Keyword(s):

Pearson Correlation ◽

Service Level ◽

Urban Rail Transit ◽

Transit Network ◽

Rail Network ◽

Topological Evolution ◽

Topological Network ◽

Urban Rail ◽

Subway System ◽

One Year

Urban rail transit (URT) system plays a significant role in daily commuting. The main features of URT could be abstracted into two kinds of networks, topological network and transit network. The correlation between topological network and transit network could represent the service level of transportation which is also a main focus to some extent. In this study, static analysis based on one year or single analysis based on one aspect are abundant, the main reason of which is the deficiency of the consistent demand data. In this regard, a comprehensive analysis of the evolution and their correlation of the two network are carried out in this work. We first revisit the topological evolution of rail network on the basis of URT network statistic indicators with a fifty-year time span. Then, based on the traditional node-place model, a correctional node-place model between demand spatial distribution and closeness centrality is established. Pearson correlation coefficient is also employed for a precise analysis. Finally, the application of the model and the corresponding analysis on Beijing Subway System (BSS) examine and evaluate the development level and service level of URT system in Beijing, and some solid evidence for relative decision-making is provided.

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Influence of Emergency Passenger Flow Distribution in Urban Rail Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.450-451.295 ◽

2012 ◽

Vol 450-451 ◽

pp. 295-301 ◽

Cited By ~ 1

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.

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Vulnerability Analysis of Urban Rail Transit Network within Multi-Modal Public Transport Networks

Sustainability ◽

10.3390/su11072109 ◽

2019 ◽

Vol 11 (7) ◽

pp. 2109 ◽

Cited By ~ 4

Author(s):

Qing-Chang Lu ◽

Shan Lin

Keyword(s):

Public Transport ◽

Flow Characteristics ◽

Urban Rail Transit ◽

Rail Transit ◽

Network Vulnerability ◽

Transit Network ◽

Rail Network ◽

Passenger Flow ◽

Urban Rail ◽

Urban Rail Transit Network

In terms of urban rail transit network vulnerability, most studies have focused on the network topology characteristics and travel cost changes after network incidents and analyzed rail transit network independently. The neglects of passenger flow distributions on the network and alternative public transport modes under rail network disruptions would either underestimate or overestimate the vulnerability of rail transit network, and thus lead to inaccurate results and decisions. This study presents an accessibility-based measurement for urban rail transit network vulnerability analysis and explicitly accounts for rail passenger flow characteristics, travel cost changes, and alternative transit modes. It is shown that the proposed approach is capable of measuring the consequences on rail network, and the advantages of the accessibility method are demonstrated and compared. The methodology is applied to the urban rail transit network of Shenzhen, China within a multi-modal public transport network. Results reveal that the consequences of disruptions on network accessibility are obviously different for stations with different passenger flow characteristics, and some undisrupted stations are found to be vulnerable under surrounding station failures. The proposed methodology offers reliable measurements on rail transit network vulnerability and implications for decision-making under rail network disruptions.

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Research on Urban Rail Transit Resource Allocation Based on K-Shortest Paths Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.748.1285 ◽

2013 ◽

Vol 748 ◽

pp. 1285-1289 ◽

Cited By ~ 2

Author(s):

Ju Mei Shen ◽

Yong Sheng Shen ◽

Lin Xu

Keyword(s):

Resource Allocation ◽

Search Algorithm ◽

Shortest Paths ◽

Flow Distribution ◽

Urban Rail Transit ◽

Rail Transit ◽

Rail Network ◽

Assignment Model ◽

Urban Rail ◽

Major Factors

This paper considers the major factors of passenger flow distribution and the running cost of train, explains and demonstrates how to sove the problem of urban rail transit resource allocation. The paper at first constructs urban rail network assignment model in the multiple operating lines based on the k-shortest paths algorithm, then proposes the k shortest paths search algorithm, finally the effectiveness of the model and algorithm are verified with the data from the Beijing urban rail transit network.

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Study on Stability of Last Train Connection under Delays on Urban Rail Transit

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.641-642.757 ◽

2014 ◽

Vol 641-642 ◽

pp. 757-762 ◽

Cited By ~ 1

Author(s):

Yuan Pei Li

Keyword(s):

Urban Rail Transit ◽

Evaluation Index System ◽

Evaluation Index ◽

Rail Transit ◽

Transit Network ◽

Rail Network ◽

Urban Rail ◽

The Stability ◽

The Impact ◽

Static Evaluation

The stability of the last train connection under delays directly reflects the coordination of urban rail network. Based on the connection of scheme of last trains, this paper analyzed of the impact of the delay on the transfers and established a static evaluation index system of the impact on transit network. Furthermore, the paper evaluated a rail transit network under different last train delays. Ultimately, the evaluation results could be got by this method, which could be used to analyze the trend of the evaluation results over delay time.

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Measuring Method of Node Importance of Urban Rail Network Based on H Index

Applied Sciences ◽

10.3390/app9235189 ◽

2019 ◽

Vol 9 (23) ◽

pp. 5189 ◽

Cited By ~ 1

Author(s):

Xiaolu Li ◽

Peng Zhang ◽

Guangyu Zhu

Keyword(s):

Measuring Method ◽

Urban Rail Transit ◽

H Index ◽

Network Nodes ◽

Rail Network ◽

Operational Risks ◽

Node Importance ◽

Urban Rail ◽

Passenger Volume ◽

Urban Rail Transit Network

Urban rail stations play an important role in passenger distribution and connectivity intervals in the network. How to effectively and reasonably evaluate their importance in the network is the key to optimizing the urban rail network structure and reducing operational risks. Taking the site as the research object and considering the topology, passenger volume, and passenger flow correlation of the urban rail network, the index of citation index is used to define node importance metric based on the h-index. Furthermore, the method of calculating the importance degree of urban rail transit network nodes based on h-index is proposed. The validity of the method is verified by the data of Beijing urban rail network in 2016, and the results are compared with the existing central index based on the network topology characteristics.

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An Algorithm for Connecting Suburban Rail Line to Urban Rail Transit Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.226-228.2349 ◽

2012 ◽

Vol 226-228 ◽

pp. 2349-2355

Author(s):

Fang Wu ◽

Bao Nan Gu

Keyword(s):

Large Scale ◽

Urban Rail Transit ◽

Transfer Coefficients ◽

Transit Network ◽

Rail Network ◽

Network Connection ◽

Urban Rail ◽

Urban Mass Transit ◽

Rail Line ◽

Connection Design

A greedy search based heuristic algorithm was proposed to solve the problem of connecting suburban rail line to existing urban mass transit network, aiming to provide efficient trips for passengers from satellite towns within metropolises to urban area. Optimum connection scheme set was sorted out from the perspectives respectively regarding optimization searching process and different transfer coefficients that reveal the predominance of transfer in path length. And at the same time, the searching process can also assure as short rail line and few connection stations be built as possible when adding more connection stations. High quality of connection design schemes can be ensured by these optional designs, which can also cover various connection modes of different station spacing, providing solid basis for evaluation and selection in future stage. Finally, the aforementioned algorithm was implemented in an example, generating an optimized connection scheme set, which proves the applicability of this algorithm in large scale rail network connection problem.

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