Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data
文献类型：期刊论文
| 作者 | Liu, Yusi1,2,3,4; Gao, Xiang1,2,3,4,5; Yi, Disheng1,2,3,4; Jiang, Heping1,2,3,4; Zhao, Yuxin1,2,3,4; Xu, Jun6; Zhang, Jing1,2,3,4 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2022-02-01 |
| 卷号 | 11期号:2页码:23 |
| 关键词 | activity semantic activity inference Bayesian rules flow clustering travel behaviors taxi trajectory |
| DOI | 10.3390/ijgi11020140 |
| 通讯作者 | Zhang, Jing(zhangjings@mail.cnu.edu.cn) |
| 英文摘要 | Massive taxi trajectory data can be easily obtained in the era of big data, which is helpful to reveal the spatiotemporal information of human travel behavior but neglects activity semantics. The activity semantics reflect people's daily activities and trip purposes, and lead to a deeper understanding of human travel patterns. Most existing literature analyses of activity semantics mainly focus on the characteristics of the destination. However, the movement from the origin to the destination can be represented as the flow. The flow can completely represent the activity semantic and describe the spatial interaction between the origin and the destination. Therefore, in this paper, we proposed a two-layer framework to infer the activity semantics of each taxi trip and generalized the similar activity semantic flow to reveal human travel patterns. We introduced the activity inference in the first layer by a combination of the improved Word2vec model and Bayesian rules-based visiting probability ranking. Then, a flow clustering method is used to uncover human travel behaviors based on the similarity of activity semantics and spatial distribution. A case study within the Fifth Ring Road in Beijing is adopted and the results show that our method is effective for taxi trip activity inference. Six activity semantics and four activity semantics are identified in origins and destinations, respectively. We also found that differences exist in the activity transitions from origins to destinations at distinct periods. The research results can inform the taxi travel demand and provide a scientific decision-making basis for taxi operation and transportation management. |
| WOS关键词 | CLUSTERING METHOD ; URBAN ; POINTS |
| WOS研究方向 | Computer Science ; Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000773697500001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/174065]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Jing |
| 作者单位 | 1.Capital Normal Univ, Coll Resources Environm & Tourism, Beijing 100048, Peoples R China 2.Capital Normal Univ, 3D Informat Collect & Applicat Key Lab, Educ Minist, Beijing 100048, Peoples R China 3.Capital Normal Univ, Beijing State Key Lab Incubat Base Urban Environm, Beijing 100048, Peoples R China 4.Capital Normal Univ, Beijing Lab Water Resources Secur, Beijing 100048, Peoples R China 5.Nanjing Bur Planning & Nat Resources, Jiangning Branch, Nanjing 211100, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Yusi,Gao, Xiang,Yi, Disheng,et al. Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2022,11(2):23. |
| APA | Liu, Yusi.,Gao, Xiang.,Yi, Disheng.,Jiang, Heping.,Zhao, Yuxin.,...&Zhang, Jing.(2022).Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,11(2),23. |
| MLA | Liu, Yusi,et al."Investigating Human Travel Patterns from an Activity Semantic Flow Perspective: A Case Study within the Fifth Ring Road in Beijing Using Taxi Trajectory Data".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 11.2(2022):23. |
入库方式： OAI收割
来源：地理科学与资源研究所
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