Understanding Human Mobility Flows from Aggregated Mobile Phone Data

被引:17
|
作者
Balzotti, Caterina [1 ]
Bragagnini, Andrea [2 ]
Briani, Maya [1 ]
Cristiani, Emiliano [1 ]
机构
[1] CNR, Ist Applicaz Calcolo, Rome, Italy
[2] TIM Serv Innovat, Turin, Italy
来源
IFAC PAPERSONLINE | 2018年 / 51卷 / 09期
关键词
Cellular data; presence data; Wasserstein distance; earth mover's distance;
D O I
10.1016/j.ifacol.2018.07.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper we deal with the study of travel flows and patterns of people in large populated areas. Information about the movements of people is extracted from coarse-grained aggregated cellular network data without tracking mobile devices individually. Mobile phone data are provided by the Italian telecommunication company TIM and consist of density profiles (i.e. the spatial distribution) of people in a given area at various instants of time. By computing a suitable approximation of the Wasserstein distance between two consecutive density profiles, we are able to extract the main directions followed by people, i.e. to understand how the mass of people distribute in space and time. The main applications of the proposed technique are the monitoring of daily flows of commuters, the organization of large events, and, more in general, the traffic management and control. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:25 / 30
页数:6
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