Travel-mode inference based on GPS-trajectory data through multi-scale mixed attention mechanism
文献类型：期刊论文
| 作者 | Pei, Xiaohui1,2; Yang, Xianjun2; Wang, Tao2 ; Ding, Zenghui2; Xu, Yang2; Jia, Lin2; Sun, Yining2
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| 刊名 | HELIYON
 |
| 出版日期 | 2024-08-15 |
| 卷号 | 10 |
| 关键词 | Travel-mode inference GPS-trajectory data Multi-scale convolution Attention mechanism |
| DOI | 10.1016/j.heliyon.2024.e35572 |
| 通讯作者 | Yang, Xianjun(xjyang@iim.ac.cn) |
| 英文摘要 | Identifying travel modes is essential for modern urban transportation planning and management. Recent advancements in data collection, especially those involving Global Positioning System (GPS) technology, offer promising opportunities for rapidly and accurately inferring users' travel modes. This study presents an innovative method for inferring travel modes from GPS trajectory data. The method utilizes multi-scale convolutional techniques to capture and analyze both temporal and spatial information of the data, thereby revealing the underlying spatiotemporal relationships inherent in user movement and behavior patterns. In addition, an attention mechanism is integrated into the model to enable autonomous learning. This mechanism enhances the model's capacity to identify and emphasize key information across different time periods and spatial locations, thus improving the accuracy of travel mode inference. Evaluation on the open-source GPS trajectory dataset, GeoLife, demonstrates that the proposed method attained an accuracy of 83.3%. This result highlights the effectiveness of the method, demonstrating that the model can more accurately understand and predict user travel modes through the integration of multi-scale convolutional technologies and attention mechanisms. |
| WOS关键词 | TRANSPORTATION MODES |
| 资助项目 | Anhui Provincial Major Science and Technology Project[202103a07020004] ; Anhui Provincial Major Science and Technology Project[202303a07020006-4] ; Anhui Provincial Major Science and Technology Project[202304a05020071] ; Anhui Province Natural Science Foundation[202204295107020004] ; National Natural Science Foundation of China[62133004] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001291368400001 |
| 出版者 | CELL PRESS |
| 资助机构 | Anhui Provincial Major Science and Technology Project ; Anhui Province Natural Science Foundation ; National Natural Science Foundation of China |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/136003]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Yang, Xianjun |
| 作者单位 | 1.Univ Sci & Technol China, 96 JinZhai Rd Baohe Dist, Hefei 230026, Anhui, Peoples R China 2.Chinese Acad Sci, Hefei Inst Phys Sci, 350 Shushanhu Rd, Hefei 230031, Anhui, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pei, Xiaohui,Yang, Xianjun,Wang, Tao,et al. Travel-mode inference based on GPS-trajectory data through multi-scale mixed attention mechanism[J]. HELIYON,2024,10. |
| APA | Pei, Xiaohui.,Yang, Xianjun.,Wang, Tao.,Ding, Zenghui.,Xu, Yang.,...&Sun, Yining.(2024).Travel-mode inference based on GPS-trajectory data through multi-scale mixed attention mechanism.HELIYON,10. |
| MLA | Pei, Xiaohui,et al."Travel-mode inference based on GPS-trajectory data through multi-scale mixed attention mechanism".HELIYON 10(2024). |
入库方式： OAI收割
来源：合肥物质科学研究院
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