著者

佐藤 大祐 松林 達史 足立 貴行 大井 伸哉 田中 悠介 長野 翔一 六藤 雄一 塩原 寿子 宮本 勝 戸田 浩之

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.35, no.2, pp.D-wd05_1-10, 2020-03-01 (Released:2020-03-01)

参考文献数

16

被引用文献数

2

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In places where many people gather, such as large-scale event venues, it is important to prevent crowd accidentsfrom occurring. To that end, we must predict the flows of people and develop remedies before congestioncreates a problem. Predicting the movement of a crowd is possible by using a multi-agent simulator, and highly accurateprediction can be achieved by reusing past event information to accurately estimate the simulation parameters.However, no such information is available for newly constructed event venues. Therefore, we propose here a methodthat improves estimation accuracy by utilizing the data measured on the current day. We introduce a people-flowprediction system that incorporates the proposed method. In this paper, we introduce results of an experiment on thedeveloped system that used people flow data measured at an actual concert event.