research-article

Temporal-spatial Analysis & Visualization of Passenger Flow after Opening New Railway Lines in Shenzhen Metro

Authors:

Maohua ZhongAuthors Info & Claims

Safety and Resilience'18: Proceedings of the 4th ACM SIGSPATIAL International Workshop on Safety and Resilience

Article No.: 4, Pages 1 - 6

https://doi.org/10.1145/3284103.3284107

Published: 06 November 2018 Publication History

Get Access

Abstract

Opening new lines will bring the structural change of passenger flow characteristics in network operation of Urban Rail Transit. Based on the smart card data from Shenzhen Metro, temporal-spatial characteristics was discussed comprehensively from different statistics dimensions and analysis angles. At the same time, passenger flow in 28 transfer stations was analyzed by clustering algorithm and the land use nature was attained. Consequently, the passenger flow law in Shenzhen Metro will be understood better combined with visualization. Especially, when facing the risk of large passenger flow, targeted measures can be taken in advance to improve the safety and resilience of Shenzhen Metro.

References

[1]

Xu Xinyue, Xie Liping, Li Haiying, Ling qiaoQin. Learning the route choice behavior of subway passengers from AFC data. Expert Systems with Applications, 2018, 95: 324--332

Crossref

Google Scholar

[2]

Jungang Shi, Lixing Yang, Jing Yang, Ziyou Gao. Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach. Transportation Research Part B: Methodological, 2018, 110: 26--59

Crossref

Google Scholar

[3]

Xue-mei Xiao, Li-min Jia, Yan-hui Wang. Correlation between heterogeneity and vulnerability of subway networks based on passenger flow. Journal of Rail Transport Planning & Management, 2018, 8: 145--157

Crossref

Google Scholar

[4]

Wenjie Wu, Jinhyun Hong. Does public transit improvement affect commuting behavior in Beijing, China? A spatial multilevel approach. Transportation Research Part D: Transport and Environment, 2017, 52: 471--479

Crossref

Google Scholar

[5]

Nuo Yong, Shunjiang Ni, Shifei Shen, Peng Chen, Xuewei Ji. Uncovering stable and occasional human mobility patterns: A case study of the Beijing subway. Physica A, 2018, 492: 28--38

Crossref

Google Scholar

[6]

Man Silk, Jin Ki Eom, Tae-Young Heo and Jiyoung Song. Intervention Analysis of the Impact of Opening a New Railway Line on Passenger Ridership in Seoul. KSCE Journal of Civil Engineering, 2016, 20 (6): 2524--2534

Crossref

Google Scholar

[7]

Shasha Liu, Enjian Yao, Xin Cheng, Yongsheng Zhang. Evaluating the impact of new lines on entrance/exit passenger flow of adjacent existing stations in urban rail transit system. Transportation Research Procedia 25C, 2017:2629--2642

Google Scholar

[8]

Blair N, Hine J, Bukhari S M A. Analyzing the impact of network change on transport disadvantage: a GIS-based case study of Belfast. Journal of Transport Geography, 2013, 31:192--200.

Crossref

Google Scholar

[9]

Yasuhiro Kojima, Takuya Matsunaga, Shuji Yamaguchi. The impact of new Shinkansen lines (Tohoku Shinkansen (Hachinohe - Shin-Aomori) and Kyusyu Shinkansen (Hakata - Shin-Yatsushiro)). Transportation Research Procedia, 2017, 25: 344--357

Crossref

Google Scholar

[10]

Pengjun Zhao, Hanzi Yang, Lu Kong, Yunshu Liu, Di Liu. Disintegration of metro and land development in transition China: A dynamic analysis in Beijing. Transportation Research Part A: Policy and Practice, 2018, 116: 290--307

Crossref

Google Scholar

[11]

Jun-tao Yang. Safety Risk Analysis and Countermeasures Study on Regular Mass Passenger Flow of China's Urban Subway. Procedia Engineering, 2016, 135: 175--179

Crossref

Google Scholar

[12]

Maohua Zhong, Congling, Shi, Xuwei Tu, Tairan Fu, Li He. Study of the human evacuation simulation of metro fire safety analysis in China. Journal of Loss Prevention in the Process Industries, 2008, 21: 287--298

Crossref

Google Scholar

[13]

Shi Congling, Zhong Maohua, Nong Xingzhong, He Li, Shi Jiehong, Feng Guoguan. Modeling and safety strategy of passenger evacuation in a metro station in China. Safety Science, 2012, 50: 1319--1332

Crossref

Google Scholar

Cited By

View all

Tian TCheng YLiang YMa CChen KHu X(2024)Hub Node Identification in Urban Rail Transit Network Evolution Using a Ridership-Weighted NetworkTransportation Research Record: Journal of the Transportation Research Board10.1177/03611981231217500Online publication date: 8-Jan-2024
https://doi.org/10.1177/03611981231217500
Meng YQi QLiu JZhou W(2022)Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021Sustainability10.3390/su1412723414:12(7234)Online publication date: 13-Jun-2022
https://doi.org/10.3390/su14127234
Meng YTian XLi ZZhou WZhou ZZhong M(2020)Exploring node importance evolution of weighted complex networks in urban rail transitPhysica A: Statistical Mechanics and its Applications10.1016/j.physa.2020.124925(124925)Online publication date: Jul-2020
https://doi.org/10.1016/j.physa.2020.124925

Index Terms

Temporal-spatial Analysis & Visualization of Passenger Flow after Opening New Railway Lines in Shenzhen Metro
1. Information systems
  1. Information systems applications
    1. Data mining
      1. Clustering
    2. Spatial-temporal systems

Recommendations

Modeling the Operation of Passenger Flow on Railway Passenger Dedicated Line Based on Multi-agents
AICI '10: Proceedings of the 2010 International Conference on Artificial Intelligence and Computational Intelligence - Volume 03

Passenger flow operation is an urgent issue to be solved for the segmental construction of passenger dedicated lines in China. In essence, passenger flow operation is the mergence and splitting of passenger flows. Therefore, this study establishes a ...
Timetable Optimization for Metro Lines Connecting to Intercity Railway Stations to Minimize Passenger Waiting Time
In major metropolitan cities, metro and intercity rail services usually share stations or have stations in close proximity to facilitate smooth connections for passengers. A large number of passengers may arrive on metro platforms within a short period of ...
A Forecast Model of Urban Passenger Flow Containing New Railway Project
PEITS '08: Proceedings of the 2008 Workshop on Power Electronics and Intelligent Transportation System

The urban passenger flow forecast is an important part of urban traffic planning. The urban passenger flow forecast containing the new railway project is much different from the common passenger flow forecast. The difficult is ascertaining the share ...

Comments

Information & Contributors

Information

Published In

Safety and Resilience'18: Proceedings of the 4th ACM SIGSPATIAL International Workshop on Safety and Resilience

November 2018

129 pages

ISBN:9781450360449

DOI:10.1145/3284103

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

National Science Foundation of China
National Outstanding Youth Science
National Key R&D Program of China

Conference

SIGSPATIAL '18

Sponsor:

SIGSPATIAL

SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 6, 2018

WA, Seattle, USA

Acceptance Rates

Safety and Resilience'18 Paper Acceptance Rate 22 of 38 submissions, 58%;

Overall Acceptance Rate 22 of 38 submissions, 58%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
142
Total Downloads

Downloads (Last 12 months)14
Downloads (Last 6 weeks)1

Reflects downloads up to 06 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Tian TCheng YLiang YMa CChen KHu X(2024)Hub Node Identification in Urban Rail Transit Network Evolution Using a Ridership-Weighted NetworkTransportation Research Record: Journal of the Transportation Research Board10.1177/03611981231217500Online publication date: 8-Jan-2024
https://doi.org/10.1177/03611981231217500
Meng YQi QLiu JZhou W(2022)Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021Sustainability10.3390/su1412723414:12(7234)Online publication date: 13-Jun-2022
https://doi.org/10.3390/su14127234
Meng YTian XLi ZZhou WZhou ZZhong M(2020)Exploring node importance evolution of weighted complex networks in urban rail transitPhysica A: Statistical Mechanics and its Applications10.1016/j.physa.2020.124925(124925)Online publication date: Jul-2020
https://doi.org/10.1016/j.physa.2020.124925

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Modeling the Operation of Passenger Flow on Railway Passenger Dedicated Line Based on Multi-agents

Timetable Optimization for Metro Lines Connecting to Intercity Railway Stations to Minimize Passenger Waiting Time

A Forecast Model of Urban Passenger Flow Containing New Railway Project

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations