Movement recommendation system based on multi-spot congestion analytics

Keita Nakayama; Akira Onoue; Maiya Hori; Atsushi Shimada; Rin ichiro Taniguchi

doi:10.3390/su12062417

Movement recommendation system based on multi-spot congestion analytics

Keita Nakayama, Akira Onoue, Maiya Hori, Atsushi Shimada, Rin ichiro Taniguchi

Research output: Contribution to journal › Article › peer-review

Abstract

Abstract: A method is proposed for resolving human congestion at a specific time at key spots in an area. Sensing data on real-world human flows are analyzed, and important information for changing movement behavior is accordingly provided. By using conventional approaches, this was a difficult task, whereas in the proposed approach, the targets and timing of providing information for congestion mitigation are determined based on spot importance. A congestion transition model is constructed from actual data and the results of a questionnaire survey. Finally, congestion mitigation in key spots is simulated after movement recommendation has been provided.

Original language	English
Article number	2417
Journal	Sustainability (Switzerland)
Volume	12
Issue number	6
DOIs	https://doi.org/10.3390/su12062417
Publication status	Published - Mar 1 2020

All Science Journal Classification (ASJC) codes

Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Management, Monitoring, Policy and Law

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/su12062417

Cite this

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title = "Movement recommendation system based on multi-spot congestion analytics",

abstract = "Abstract: A method is proposed for resolving human congestion at a specific time at key spots in an area. Sensing data on real-world human flows are analyzed, and important information for changing movement behavior is accordingly provided. By using conventional approaches, this was a difficult task, whereas in the proposed approach, the targets and timing of providing information for congestion mitigation are determined based on spot importance. A congestion transition model is constructed from actual data and the results of a questionnaire survey. Finally, congestion mitigation in key spots is simulated after movement recommendation has been provided.",

author = "Keita Nakayama and Akira Onoue and Maiya Hori and Atsushi Shimada and Taniguchi, {Rin ichiro}",

note = "Funding Information: Acknowledgments: This research was partially supported by AdInte Co., Ltd. Funding Information: This research received no external funding. This research was partially supported by AdInte Co., Ltd. Publisher Copyright: {\textcopyright} 2020 by the authors.",

year = "2020",

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doi = "10.3390/su12062417",

language = "English",

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T1 - Movement recommendation system based on multi-spot congestion analytics

AU - Nakayama, Keita

AU - Onoue, Akira

AU - Hori, Maiya

AU - Shimada, Atsushi

AU - Taniguchi, Rin ichiro

N1 - Funding Information: Acknowledgments: This research was partially supported by AdInte Co., Ltd. Funding Information: This research received no external funding. This research was partially supported by AdInte Co., Ltd. Publisher Copyright: © 2020 by the authors.

PY - 2020/3/1

Y1 - 2020/3/1

N2 - Abstract: A method is proposed for resolving human congestion at a specific time at key spots in an area. Sensing data on real-world human flows are analyzed, and important information for changing movement behavior is accordingly provided. By using conventional approaches, this was a difficult task, whereas in the proposed approach, the targets and timing of providing information for congestion mitigation are determined based on spot importance. A congestion transition model is constructed from actual data and the results of a questionnaire survey. Finally, congestion mitigation in key spots is simulated after movement recommendation has been provided.

AB - Abstract: A method is proposed for resolving human congestion at a specific time at key spots in an area. Sensing data on real-world human flows are analyzed, and important information for changing movement behavior is accordingly provided. By using conventional approaches, this was a difficult task, whereas in the proposed approach, the targets and timing of providing information for congestion mitigation are determined based on spot importance. A congestion transition model is constructed from actual data and the results of a questionnaire survey. Finally, congestion mitigation in key spots is simulated after movement recommendation has been provided.

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JO - Sustainability

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ER -

Movement recommendation system based on multi-spot congestion analytics

Abstract

All Science Journal Classification (ASJC) codes

UN SDGs

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