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abstract

Metropolitan-scale Mobility Digital Twin

Published: 27 February 2023 Publication History

Abstract

Mobility digital twin, which is a a virtual replica of the mobility in the physical world, is the key building block of modern smart city applications at a metropolitan scale, including traffic regulation, emergency management and epidemic control. To duplicate the mobility in the physical world and show the potential outcome based on either the current state or manipulated conditions, we are facing with three main challenges: 1) how to sense real-time human mobility at a large scale and assimilate different data sources to infer a dynamic city mobility state; 2) how to make an accurate prediction for the mobility replica that adapts with dynamic city mobility state; 3) how to simulate the mobility in response to different conditions. In this talk, we will present our recent studies, practices and perspectives on mobility digital twin in addressing these above challenges, with applications in the real-world scenarios with industrial connections.

Supplementary Material

MP4 File (wsdm2023_special_fan_metropolitan_scale_01.mp4-streaming.mp4)
Metropolitan-scale Mobility Digital Twin

References

[1]
Quanjun Chen, Renhe Jiang, Chuang Yang, Zekun Cai, Zipei Fan, Kota Tsubouchi, Ryosuke Shibasaki, and Xuan Song. 2020. Dualsin: Dual sequential interaction network for human intentional mobility prediction. In Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 283--292.
[2]
Zipei Fan, Xuan Song, Ryosuke Shibasaki, Tao Li, and Hodaka Kaneda. 2016. CityCoupling: bridging intercity human mobility. In Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing. 718--728.
[3]
Zipei Fan, Xuan Song, Tianqi Xia, Renhe Jiang, Ryosuke Shibasaki, and Ritsu Sakuramachi. 2018. Online deep ensemble learning for predicting citywide human mobility. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 3 (2018), 1--21.
[4]
Zipei Fan, Xiaojie Yang, Wei Yuan, Renhe Jiang, Quanjun Chen, Xuan Song, and Ryosuke Shibasaki. 2022. Online Trajectory Prediction for Metropolitan Scale Mobility Digital Twin. In Proceedings of the 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.
[5]
Renhe Jiang, Quanjun Chen, Zekun Cai, Zipei Fan, Xuan Song, Kota Tsubouchi, and Ryosuke Shibasaki. 2020. Will you go where you search? a deep learning framework for estimating user search-and-go behavior. Neurocomputing (2020).
[6]
Renhe Jiang, Jing Zhao, Tingting Dong, Yoshiharu Ishikawa, Chuan Xiao, and Yuya Sasaki. 2015. A density-based approach for mining movement patterns from semantic trajectories. In TENCON 2015--2015 IEEE Region 10 Conference. IEEE, 1--6.
[7]
Chuang Yang, Zhiwen Zhang, Zipei Fan, Renhe Jiang, Quanjun Chen, Xuan Song, and Ryosuke Shibasaki. 2022. EpiMob: Interactive Visual Analytics of Citywide Human Mobility Restrictions for Epidemic Control. IEEE Transactions on Visualization and Computer Graphics (2022).

Cited By

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  • (2024)Business Models Used in Smart Cities—Theoretical Approach with Examples of Smart CitiesSmart Cities10.3390/smartcities70400657:4(1626-1669)Online publication date: 1-Jul-2024

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Published In

cover image ACM Conferences
WSDM '23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining
February 2023
1345 pages
ISBN:9781450394079
DOI:10.1145/3539597
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 February 2023

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Author Tags

  1. mobility digital twin
  2. mobility prediction
  3. mobility simulation
  4. trajectory mining

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WSDM '23

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Overall Acceptance Rate 498 of 2,863 submissions, 17%

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  • (2024)Business Models Used in Smart Cities—Theoretical Approach with Examples of Smart CitiesSmart Cities10.3390/smartcities70400657:4(1626-1669)Online publication date: 1-Jul-2024

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