Spatio-Temporal Clustering of Time-Dependent Origin-Destination Electronic Trace Data

被引：0

作者：

van Leeuwen, Daphne ^{[1
,2
]}

Bosman, Joost ^{[1
]}

Dugundji, Elenna ^{[1
,2
]}

机构：

[1] Ctr Wiskunde & Informat, Sci Pk 123, NL-1098 XG Amsterdam, Netherlands

[2] Vrije Univ, De Boelelaan 1081-1087, NL-1081 HV Amsterdam, Netherlands

来源：

9TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2018) / THE 8TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2018) / AFFILIATED WORKSHOPS | 2018年 / 130卷

关键词：

Screen-lines; OD-matrices; Clustering; Modularity optimization; GPS traces; Travel behavior;

D O I：

10.1016/j.procs.2018.04.053

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study we identify spatial regions based on an empirical data set consisting of time-dependent origin-destination (OD) pairs. This OD data consists of electronic traces collected from smart phone data by Google in the Amsterdam metropolitan region and is aggregated by the volume of trips per hour at neighborhood level. In this study we cluster the pairs by space and time to gain insight in both aspects regarding travel characteristics. We show that spatially connected clusters appear when we use a performance metric called modularity on the OD data when directionality is incorporated. (C) 2018 The Authors. Published by Elsevier B.V.

引用

页码：359 / 367

页数：9

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