NDLI: Resident activity pattern recognition and comparison of six Sino-American metropolises

Content Provider	IET Digital Library
Author	Yang, Chao Ye, Wen Zhu, Rongrong Zhang, Tianran
Abstract	Travel decision making is driven by different activities. To better understand the traffic-activity characteristics of different regions, representative activity patterns (RAPs) of six Sino-American metropolises are recognised, and then these metropolises are clustered for each kind of RAP. Same year's National Household Travel Survey data of USA and Shanghai Household Travel Survey (SHTS) data are used in this study. Each resident's activity-topic probability distribution could be obtained by latent Dirichlet allocation topic model, then residents’ RAPs of a region are recognised by affinity propagation clustering, for each region's weekdays and weekends, respectively. Based on RAPs recognition, the six metropolises are clustered within conspecific RAP according to the dissimilarity of pattern characteristics (the number of per capita activities, sex ratio etc.). At last, six metropolises are divided into three, two, five clusters in accordance with three kinds of work patterns, which are weekdays’ normal work pattern, weekdays’ late return (home) work pattern, and weekends’ work pattern. Regions in the same cluster have homologous demographic compositions and show similar activity characteristics.
Starting Page	443
Ending Page	452
Page Count	10
ISSN	1751956X
Volume Number	13
e-ISSN	17519578
Issue Number	Issue 3, Mar (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/13/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.5246
Journal	IET Intelligent Transport Systems
Publisher Date	2018-09-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Activity-topic Probability Distribution Administration of Other Service Industries Affinity Propagation Clustering Data Handling Technique Decision Making Latent Dirichlet Allocation Topic Model National Household Travel Survey Data of USA Number-of-per Capita Activities Pattern Characteristic Pattern Clustering RAP Recognition Representative Activity Pattern Sex Ratio Shanghai Household Travel Survey Data Sino-American Metropolises Statistical Distribution Statistics Traffic Engineering Computing Traffic-activity Characteristic Travel Decision Making Travel Industry Weekdays Late Return Work Pattern Weekdays Normal Work Pattern Weekends Work Pattern
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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