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カワイ ユキコ
KAWAI YUKIKO
河合 由起子 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2014/11/04 |
| 形態種別 | 研究論文（国際会議プロシーディングス） |
| 査読 | 査読あり |
| 標題 | Crowd-sourced prediction of pedestrian congestion for bike navigation systems |
| 執筆形態 | その他 |
| 掲載誌名 | Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoStreaming, IWGS 2014 |
| 出版社・発行元 | Association for Computing Machinery, Inc |
| 巻・号・頁 | pp.25-32 |
| 著者・共著者 | Shoko Wakamiya,Yukiko Kawai,Hiroshi Kawasaki,Ryong Lee,Kazutoshi Sumiya,Toyokazu Akiyama |
| 概要 | GPS-based navigation systems widely available on automobiles and smartphones nowadays are essential to find the best routes in the complicated urban space. However, it is still difficult for bikers to take full advantages of such navigation systems due to the lack of consideration on the different driving conditions. Generally, motorcyclists and cyclists take rides on narrow alleys and sidewalks which have a high risk of bumping against pedestrians. Therefore, it is necessary to find comfortable driving routes, also possibly avoiding areas congested by crowds. However, it is impractical to monitor crowd's existence everywhere at all times for such crowd-aware navigation. To overcome this limitation, we attempt to utilize location-based social network services where geo-tagged microblogs from massive crowd can be a good alternative source to measure pedestrian congestion in urban areas. In this paper, we introduce a route search method for bikers particularly to exploit crowd's volunteering reports being streamed via microblogs. In order to estimate human traffic from microblogs, we develop a crowd flow network which captures probable crowd movement on an urban network. We also examine the possible intersections which are expected to be highly congested based on the model. On the crowd flow network, we will find the best routes consisting of comfortable intersections and streets for the bike navigation systems. |
| DOI | 10.1145/2676552.2676562 |
| DBLP ID | conf/gis/WakamiyaKKLSA14 |
| PermalinkURL | http://dblp.uni-trier.de/db/conf/gis/iwgs2014.html#conf/gis/WakamiyaKKLSA14 |