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Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling
Liu, Kang1,2; Gao, Song3; Lu, Feng2,4,5,6
2019-03-01
Source PublicationCOMPUTERS ENVIRONMENT AND URBAN SYSTEMS
ISSN0198-9715
Volume74Pages:50-61
Corresponding AuthorLu, Feng(luf@lreis.ac.cn)
AbstractThe 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.
KeywordSpatial interaction Vehicle movement Stroke Road network Topic model
DOI10.1016/j.compenvurbsys.2018.12.001
WOS KeywordSTREET NETWORKS ; PATH SELECTION ; MOBILITY
Indexed BySCI
Language英语
Funding ProjectNational 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]
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program
WOS Research AreaComputer Science ; Engineering ; Environmental Sciences & Ecology ; Geography ; Operations Research & Management Science ; Public Administration
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Environmental ; Environmental Studies ; Geography ; Operations Research & Management Science ; Regional & Urban Planning
WOS IDWOS:000458227000005
PublisherELSEVIER SCI LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49950
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLu, Feng
Affiliation1.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
Recommended Citation
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.
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