Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling

doi:10.1016/j.compenvurbsys.2018.12.001

	Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling
	Liu, Kang 1,2; Gao, Song 3; Lu, Feng 2,4,5,6
刊名	COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
	2019-03-01
卷号	74 页码:50-61
关键词	Spatial interaction Vehicle movement Stroke Road network Topic model
ISSN号	0198-9715
DOI	10.1016/j.compenvurbsys.2018.12.001
通讯作者	Lu, Feng(luf@lreis.ac.cn)
英文摘要	The development of mobile positioning technologies makes massive individual trajectory data easily accessible, which facilitates the revisit of spatial interaction issue in recent years. Researchers have proposed many methods to investigate the spatial interactions derived from human movements, such as the gravity model and radiation model. However, these studies have mainly focused on the interactions among areal units at an aggregated level, neglecting that in most cases, human movements are carried by vehicles and constrained by the underlying road network, which causes the interactions among roads. To fill this gap, we propose a novel approach to identify spatial interaction patterns of vehicle movements on urban road network. As the topic model originating from the domain of natural language processing has powerful advantages in extracting semantic relations of words from corpus, we utilize it to extract interaction relations of urban roads from massive vehicle trajectories. First, "strokes" (i.e., natural streets) are chosen as geographical units to represent the vehicle moving paths. Then, an analogy between geographical elements (i.e., stroke, moving path) and textual elements (i.e., word, document) is established, and a topic model is applied to the moving paths to identify the spatial interaction patterns on road network. From a mass of trajectory data collected by GNSS-equipped taxis in Beijing, the "topic patterns", which can be viewed as clusters of spatially interacted strokes, are identified, visualized and verified. It is argued that our proposed approach is effective in identifying spatial interaction patterns, which provides a new perspective for spatial interaction modelling and enriches the current spatial interaction studies.
资助项目	National Natural Science Foundation of China[41631177] ; National Natural Science Foundation of China[41601421] ; National Natural Science Foundation of China[41701167] ; National Key Research and Development Program[2016YFB0502104]
WOS关键词	STREET NETWORKS ; PATH SELECTION ; MOBILITY
WOS研究方向	Computer Science ; Engineering ; Environmental Sciences & Ecology ; Geography ; Operations Research & Management Science ; Public Administration
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000458227000005
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/49949]
专题	中国科学院地理科学与资源研究所
通讯作者	Lu, Feng
作者单位	1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 3.Univ Wisconsin Madison, Dept Geog, Madison, WI USA 4.Fujian Collaborat Innovat Ctr Big Data Applicat G, Fuzhou, Fujian, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China 6.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Liu, Kang,Gao, Song,Lu, Feng. Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling[J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,2019,74:50-61.
APA	Liu, Kang,Gao, Song,&Lu, Feng.(2019).Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling.COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,74,50-61.
MLA	Liu, Kang,et al."Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling".COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 74(2019):50-61.