Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/96496
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Logistics and Maritime Studies | - |
dc.creator | Zhang, J | en_US |
dc.creator | Wu, W | en_US |
dc.creator | Cheng, Q | en_US |
dc.creator | Tong, W | en_US |
dc.creator | Khadka, A | en_US |
dc.creator | Fu, X | en_US |
dc.creator | Gu, Z | en_US |
dc.date.accessioned | 2022-12-07T02:55:12Z | - |
dc.date.available | 2022-12-07T02:55:12Z | - |
dc.identifier.issn | 0197-6729 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/96496 | - |
dc.language.iso | en | en_US |
dc.publisher | John Wiley & Sons | en_US |
dc.rights | © 2022 Junwei Zhang et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.rights | The following publication Zhang, J., Wu, W., Cheng, Q., Tong, W., Khadka, A., Fu, X., & Gu, Z. (2022). Extracting the Complete Travel Trajectory of Subway Passengers Based on Mobile Phone Data. Journal of Advanced Transportation, 2022, 8151520 is available at https://doi.org/10.1155/2022/8151520. | en_US |
dc.title | Extracting the complete travel trajectory of subway passengers based on mobile phone data | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 2022 | en_US |
dc.identifier.doi | 10.1155/2022/8151520 | en_US |
dcterms.abstract | The usage of mobile phones has undergone tremendous growth in the past decades. Large amounts of mobile-phone signaling data (MSD) are generated while using various mobile phone applications. The large-scale MSD presents opportunities for transport planners to utilize it for better planning and management of the transportation system. In this paper, we use MSD to analyze subway passengers’ travel behavior and extract their complete travel trajectories. The complete travel trajectories of subway passengers include their trajectories, both inside and outside the subway system. In the first stage, the MSD from the subway base stations is selected, sorted by time, and the rough trajectory in the subway system is extracted. The ground base stations around the subway station are then considered to correct the boarding and alighting subway stations in order to obtain a more detailed trajectory. In the second stage, the service range of the base station is determined according to the Thiessen polygon, and a temporal dynamic threshold is proposed to extract the passenger’s stop point outside the subway system. Finally, the complete trajectories of subway passengers are obtained. The proposed algorithms are verified using a set of MSD collected in Suzhou, China. The results show that the proposed algorithms can effectively extract the complete travel trajectory of subway passengers. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of advanced transportation, 25 Jan. 2022, v. 2022, 8151520 | en_US |
dcterms.isPartOf | Journal of advanced transportation | en_US |
dcterms.issued | 2022-01-25 | - |
dc.identifier.scopus | 2-s2.0-85124493279 | - |
dc.identifier.eissn | 2042-3195 | en_US |
dc.identifier.artn | 8151520 | en_US |
dc.description.validate | 202212 bckw | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | - |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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8151520.pdf | 2.27 MB | Adobe PDF | View/Open |
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