Modeling Human Spatial Mobility Patterns with the Lévy Flight Cluster Model
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| author | Wolff, Malcolm Dobra, Adrian Westveld, Anton H. Chiu, Grace S. |
| author_facet | Wolff, Malcolm Dobra, Adrian Westveld, Anton H. Chiu, Grace S. |
| contents | Despite the extensive collection of individual mobility data over the past decade, fueled by the widespread use of GPS-enabled personal devices, the existing statistical literature on estimating human spatial mobility patterns from temporally irregular location data remains limited. In this paper, we introduce the Lévy Flight Cluster Model (LFCM), a hierarchical Bayesian mixture model designed to analyze an individual's activity distribution. The LFCM can be utilized to determine probabilistic overlaps between individuals' activity patterns and serves as an anonymization tool to generate synthetic location data. We present our methodology using real-world human location data, demonstrating its ability to accurately capture the key characteristics of human movement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_00298 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modeling Human Spatial Mobility Patterns with the Lévy Flight Cluster Model Wolff, Malcolm Dobra, Adrian Westveld, Anton H. Chiu, Grace S. Methodology Applications 62G07, 62P25, 91C99 Despite the extensive collection of individual mobility data over the past decade, fueled by the widespread use of GPS-enabled personal devices, the existing statistical literature on estimating human spatial mobility patterns from temporally irregular location data remains limited. In this paper, we introduce the Lévy Flight Cluster Model (LFCM), a hierarchical Bayesian mixture model designed to analyze an individual's activity distribution. The LFCM can be utilized to determine probabilistic overlaps between individuals' activity patterns and serves as an anonymization tool to generate synthetic location data. We present our methodology using real-world human location data, demonstrating its ability to accurately capture the key characteristics of human movement. |
| title | Modeling Human Spatial Mobility Patterns with the Lévy Flight Cluster Model |
| topic | Methodology Applications 62G07, 62P25, 91C99 |
| url | https://arxiv.org/abs/2509.00298 |