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Title: | Tensor Decomposition for Spatiotemporal Mobility Pattern Learning with Mobile Phone Data | Authors: | Gong, Suxia Saadi, Ismail Teller, Jacques COOLS, Mario |
Issue Date: | 2024 | Publisher: | SAGE PUBLICATIONS INC | Source: | Transportation Research Record, | Status: | Early view | Abstract: | Detecting urban mobility patterns is crucial for policymakers in urban and transport planning. Mobile phone data have been increasingly deployed to measure the spatiotemporal variations in human mobility. This work applied non-negative Tucker decomposition (NTD) to mobile phone-based origin-destination (O-D) matrices to explore mobility patterns' latent spatial and temporal relationships in the province of Li & egrave;ge, Belgium. Four 310 x 310 x 24 traffic tensors have been built for one regular weekday, one regular weekend day, one holiday weekday, and one holiday weekend day, respectively. The proposed method inferred spatial clusters and temporal patterns while interpreting the correlation between spatial clusters and temporal patterns through geographical visualization. As a result, we found the similarity of O-D and destination-origin (D-O) patterns and the symmetry for the trips of the temporal patterns with evening peak and morning peaks on the weekday. Moreover, we investigated the attraction of different spatial clusters with two temporal patterns on a regular weekday and validated the reconstructed demand using population counts and commuting matrices. Finally, the differences in spatial and temporal interactions have been addressed in detail. | Notes: | Gong, SX (corresponding author), Univ Liege, Dept Urban & Environm Engn, LEMA Res Grp, Liege, Belgium. suxia.gong@uliege.be |
Keywords: | data and data science;urban transportation data and information systems;data analysis;data validation;planning and analysis;transportation demand management;travel demand modeling | Document URI: | http://hdl.handle.net/1942/43694 | ISSN: | 0361-1981 | e-ISSN: | 2169-4052 | DOI: | 10.1177/03611981241270166 | ISI #: | 001290599100001 | Rights: | The Author(s) 2024 | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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Tensor Decomposition for Spatiotemporal Mobility Pattern Learning with Mobile Phone Data.pdf Restricted Access | Early view | 6.85 MB | Adobe PDF | View/Open Request a copy |
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