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: | Hui Zhou, Zhihao Zheng, Xuekai Cen, Zhiren Huang, Pu Wang |
---|---|
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!
|
Similar Items
-
Data-Driven Synchronization Analysis of a Bouncing Crowd
by: Jun Chen, et al.
Published: (2019-01-01) -
Crowd Density Estimation of Scenic Spots Based on Multifeature Ensemble Learning
by: Xiaohang Xu, et al.
Published: (2017-01-01) -
A data fusion-based method for pedestrian detection and flow statistics across different crowd densities
by: Ranpeng Wang, et al.
Published: (2025-03-01) -
Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling
by: He Wang, et al.
Published: (2025-12-01) -
Task Grid-Based Urban Environmental Information Release Mechanism for Mobile Crowd Sensing
by: Zhenwei Chen, et al.
Published: (2022-01-01)