2022 Fiscal Year Final Research Report
Development of a system to steer crowds through imperceptible modifications of the surrounding environment
| Project/Area Number |
20K14992
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 25020:Safety engineering-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Feliciani Claudio 東京大学, 先端科学技術研究センター, 特任准教授 (40870035)
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | crowd / swarm / collective behavior / emergent behavior / complex systems / environment / nudge |
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| Outline of Final Research Achievements |
This research aimed to understand whether it is possible to influence crowd motion by using minor environmental stimuli (light, color, etc.). It has been found that, in a limited extent, such an approach is possible. However, both crowd density and interaction time (with the environment) play an important role. Furthermore, a density which allows interactions between people is needed and time must be long enough to allow the emergence of self-organization.
The conclusions could be obtained through several experiments and by examining old data through intuitions found while working on this research. An experiment unsuccessfully attempted to steer individuals in a familiar environment. But, experiments with animals swarms helped providing some hints on conditions where steering may work. Results showed that at medium densities optimal steering found. By revisiting old experiments it was hinted that, in controlled conditions, interaction between people is needed for an effective steering.
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| Free Research Field |
complex systems
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| Academic Significance and Societal Importance of the Research Achievements |
This research has helped showing that unconventional ways to steer people are viable. In addition, it also showed that by working on areas of research which are different and complementary (human crowds and animal swarms here) can help to create a robust theory and formulate more likely hypotheses.
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