Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling
文献类型：期刊论文
| 作者 | Liu, Kang1,2; Gao, Song3; Lu, Feng2,4,5,6
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| 刊名 | COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
 |
| 出版日期 | 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. |
| WOS关键词 | STREET NETWORKS ; PATH SELECTION ; MOBILITY |
| 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研究方向 | Computer Science ; Engineering ; Environmental Sciences & Ecology ; Geography ; Operations Research & Management Science ; Public Administration |
| 语种 | 英语 |
| WOS记录号 | WOS:000458227000005 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program |
| 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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