Reconstruction of People Flow in Areas of Incomplete Data Availability

被引：1

作者：

Xu, Yongwei ^{[1
]}

Shibasaki, Ryosuke ^{[1
]}

Shao, Xiaowei ^{[2
]}

机构：

[1] Univ Tokyo, Ctr Spatial Informat Sci, Kashiwa, Chiba, Japan

[2] Univ Tokyo, Earth Observat Data Integrat & Fus Res Initiat, Meguro Ku, Tokyo, Japan

来源：

2015 IEEE 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS | 2015年

关键词：

people flow; data assimilation; incomplete areas; SOCIAL FORCE MODEL; JAMMING TRANSITION; ASSIGNMENT; SIMULATION; DYNAMICS;

D O I：

10.1109/ITSC.2015.183

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

Data Assimilation is a technique that synthesizes information from a dynamic (numerical) model and observation data. To reconstruct people flow in areas that are partially invisible to sensors, we assess three data assimilation methods: Kalman filter, 3DVAR, and particle filter. While most studies focus on individual -based analysis, in this study, we process the movement of people using a dynamic continuum flow theory. We derive the dynamic model of people flow and numerically solve it using the data assimilation method. Our proposed method is validated in 1D and 2D simulation experiments and on real tracking data.

引用

页码：1104 / 1110

页数：7

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