A Data-Driven Urban Metro Management Approach for Crowd Density Control
Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the a...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/6675605 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832550087073464320 |
|---|---|
| author | Hui Zhou Zhihao Zheng Xuekai Cen Zhiren Huang Pu Wang |
| author_facet | Hui Zhou Zhihao Zheng Xuekai Cen Zhiren Huang Pu Wang |
| author_sort | Hui Zhou |
| collection | DOAJ |
| description | Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range. |
| format | Article |
| id | doaj-art-8f4f17701ce5499caf0003c2d79e67ec |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-8f4f17701ce5499caf0003c2d79e67ec2025-02-03T06:07:40ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/66756056675605A Data-Driven Urban Metro Management Approach for Crowd Density ControlHui Zhou0Zhihao Zheng1Xuekai Cen2Zhiren Huang3Pu Wang4School of Traffic and Transportation Engineering, Rail Data Research and Application Key Laboratory of Hunan Province, Central South University, Changsha 410000, ChinaDepartment of Civil Engineering and Applied Mechanics, McGill University, Montreal H3A 0C3, Quebec, CanadaSchool of Traffic and Transportation Engineering, Rail Data Research and Application Key Laboratory of Hunan Province, Central South University, Changsha 410000, ChinaSchool of Traffic and Transportation Engineering, Rail Data Research and Application Key Laboratory of Hunan Province, Central South University, Changsha 410000, ChinaSchool of Traffic and Transportation Engineering, Rail Data Research and Application Key Laboratory of Hunan Province, Central South University, Changsha 410000, ChinaLarge crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.http://dx.doi.org/10.1155/2021/6675605 |
| spellingShingle | Hui Zhou Zhihao Zheng Xuekai Cen Zhiren Huang Pu Wang A Data-Driven Urban Metro Management Approach for Crowd Density Control Journal of Advanced Transportation |
| title | A Data-Driven Urban Metro Management Approach for Crowd Density Control |
| title_full | A Data-Driven Urban Metro Management Approach for Crowd Density Control |
| title_fullStr | A Data-Driven Urban Metro Management Approach for Crowd Density Control |
| title_full_unstemmed | A Data-Driven Urban Metro Management Approach for Crowd Density Control |
| title_short | A Data-Driven Urban Metro Management Approach for Crowd Density Control |
| title_sort | data driven urban metro management approach for crowd density control |
| url | http://dx.doi.org/10.1155/2021/6675605 |
| work_keys_str_mv | AT huizhou adatadrivenurbanmetromanagementapproachforcrowddensitycontrol AT zhihaozheng adatadrivenurbanmetromanagementapproachforcrowddensitycontrol AT xuekaicen adatadrivenurbanmetromanagementapproachforcrowddensitycontrol AT zhirenhuang adatadrivenurbanmetromanagementapproachforcrowddensitycontrol AT puwang adatadrivenurbanmetromanagementapproachforcrowddensitycontrol AT huizhou datadrivenurbanmetromanagementapproachforcrowddensitycontrol AT zhihaozheng datadrivenurbanmetromanagementapproachforcrowddensitycontrol AT xuekaicen datadrivenurbanmetromanagementapproachforcrowddensitycontrol AT zhirenhuang datadrivenurbanmetromanagementapproachforcrowddensitycontrol AT puwang datadrivenurbanmetromanagementapproachforcrowddensitycontrol |