著者

清水 仁 松林 達史 納谷 太 澤田 宏

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.34, no.5, pp.wd-B_1-8, 2019-09-01 (Released:2019-09-01)

参考文献数

33

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The theme park problem is a platform where methods of guiding visitors to relieve congestion are developed and evaluated by reproducing a crowded theme park on a computer. In the theme park problem, the attraction selection model is an important element in the simulator. In previous studies, multinomial logit model was mainly used for attraction selection. However, when we observed real amusement parks, we found that we can not reproduce the characteristics of waiting time of real attraction by this model. In this research, we propose a multinomial linear model as a model of attraction selection. This model can express the rational behavior of visitors that waits for a while when waiting times of all attractions are too long for them. We showed that this model can reproduce characteristics of waiting time using multiagent simulator (MAS). We also developed a method to estimate the parameters of the proposed model from the aggregated data of the output of MAS. As a result of numerical experiments, it was confirmed that the performance of the parameter estimation was good. The proposed model and method for parameter estimation can be applied not only to the theme park problem but also to various problems related to human behavior of selection.

著者

松林 達史 清武 寛 幸島 匡宏 戸田 浩之 田中 悠介 六藤 雄一 塩原 寿子 宮本 勝 清水 仁 大塚 琢馬 岩田 具治 澤田 宏 納谷 太 上田 修功

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.34, no.5, pp.wd-F_1-11, 2019-09-01 (Released:2019-09-01)

参考文献数

29

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Forming security plans for crowd navigation is essential to ensure safety management at large-scale events. The Multi Agent Simulator (MAS) is widely used for preparing security plans that will guide responses to sudden and unexpected accidents at large events. For forming security plans, it is necessary that we simulate crowd behaviors which reflects the real world situations. However, the crowd behavior situations require the OD information (departure time, place of Origin, and Destination) of each agent. Moreover, from the viewpoint of protection of personal information, it is difficult to observe the whole trajectories of all pedestrians around the event area. Therefore, the OD information should be estimated from the several observed data which is counted the number of passed people at the fixed points.In this paper, we propose a new method for estimating the OD information which has following two features. Firstly, by using Bayesian optimization (BO) which is widely used to find optimal hyper parameters in the machine learning fields, the OD information are estimated efficiently. Secondly, by dividing the time window and considering the time delay due to observation points that are separated, we propose a more accurate objective function.We experiment the proposed method to the projection-mapping event (YOYOGI CANDLE 2020), and evaluate the reproduction of the people flow on MAS. We also show an example of the processing for making a guidance plan to reduce crowd congestion by using MAS.

著者

角田 達彦 清水 仁 長尾 眞

出版者

一般社団法人情報処理学会

雑誌

情報処理学会研究報告自然言語処理(NL)

巻号頁・発行日

vol.1997, no.4, pp.129-136, 1997-01-20

被引用文献数

2

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本稿では,六法全書法律文の大局的構造の解析と要件の意味推定を表層的手がかりによって行なう手法を提案する.文の構成要素を主題,要件,効果に分け,それらが対比構造をなしているかを調べ,その結果によって各主題や要件の係り先を特定する.そして各要件の機能表現によって要件のさす内容を特定する.同時に主題の連体修飾部や,効果部に入りこんだ要件の抽出を行なう.その結果,六法全書の条文181文の学習コーパスに対して170文(3%)が,そして275文のテストコーパスに対して224文(1%)が正しく解析できた.また,とりたて助詞「は」と読点の有無が対比構造の生成・認識の鍵となり,それによって係り先が決定されることを明らかにした.We propose a method of automatic detection of global structure and semantical logics in legal sentences. Firstly, the method extracts elements in them and classifies them into three types: subject, condition, and effect. Second, it checks whether they have comparison structures, and, depending on the result, specifies their dependency. Finally, it grasps their contents using surface clues and extracts conditions from the subject and effect parts. Our method achieved 93% correctness for 181 training sentences, and 81% correctness for 275 unseen sentences. We also clarified the importance of particle 'ha' and commas for generating and understanding comparison structure, which decides phrase dependency.

著者

山岡 泰幸 青木 久美子 高橋 秀明 清水 仁 Yasuyuki Yamaoka Kumiko Aoki Hideaki Takahashi Hitoshi Shimizu

雑誌

放送大学研究年報 = Journal of The Open University of Japan

巻号頁・発行日

no.36, pp.127-138, 2019-03-25

著者

清水仁三郎 著

出版者

太閤堂

巻号頁・発行日

1913

著者

清水 仁 松林 達史 納谷 太

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

巻号頁・発行日

vol.32, no.5, pp.AG16-F_1-8, 2017

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<p>In this research, we show a paradox of the "theme park" problem. In the crowded amusement park, it is generally believed that the equalization of queue lines of people can decrease the waiting time for riding on attraction. However, the equalization of queue lines occasionally increases the waiting time in the case where congestion degree is over the limit of capacity. This paradox makes it difficult to reduce congestion. In this paper, we propose a method to reduce the waiting time even in the "theme park paradox" situation, and evaluate effectiveness of our method by multiagent simulation.</p>

著者

小山 嘉一朗 海老原 新一 清水 仁

出版者

分離技術会

雑誌

分離技術 (ISSN:13437860)

巻号頁・発行日

vol.39, no.6, pp.393-395, 2009