Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data
Over the last two decades, mobile phone data have appeared to be a promising data source for mobility analysis. The structure, abundance, and accessibility of call detail records (CDRs) make them particularly suitable for such use. However, their exploitation is often limited to estimating origin–de...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Future Transportation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7590/3/1/15 |
| _version_ | 1827749625633701888 |
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| author | Manon Seppecher Ludovic Leclercq Angelo Furno Thamara Vieira da Rocha Jean-Marc André Jérôme Boutang |
| author_facet | Manon Seppecher Ludovic Leclercq Angelo Furno Thamara Vieira da Rocha Jean-Marc André Jérôme Boutang |
| author_sort | Manon Seppecher |
| collection | DOAJ |
| description | Over the last two decades, mobile phone data have appeared to be a promising data source for mobility analysis. The structure, abundance, and accessibility of call detail records (CDRs) make them particularly suitable for such use. However, their exploitation is often limited to estimating origin–destination matrices of a restricted part of the population: regular travellers. Although these studies provide valuable information for policymakers, their scope remains limited to this subpopulation analysis. In the present work, we develop a collective mobility reconstruction method adapted to nonregular travellers. The method relies on the notion of the detour ratio, which makes it robust to the lack of mobile phone data as well as its application to large instances (large and dense telecommunication networks). It is used to conduct a longitudinal analysis of the macroscopic mobility patterns in Santiago de Cali, Colombia, thanks to call detail data shared by communication provider CLARO as part of a research project conducted by Citepa, Paris, the Green City Big Data Project. |
| first_indexed | 2024-03-11T06:31:12Z |
| format | Article |
| id | doaj.art-91f3938fb0624ab486238989cda38bb6 |
| institution | Directory Open Access Journal |
| issn | 2673-7590 |
| language | English |
| last_indexed | 2024-03-11T06:31:12Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Transportation |
| spelling | doaj.art-91f3938fb0624ab486238989cda38bb62023-11-17T11:13:49ZengMDPI AGFuture Transportation2673-75902023-02-013125427310.3390/futuretransp3010015Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone DataManon Seppecher0Ludovic Leclercq1Angelo Furno2Thamara Vieira da Rocha3Jean-Marc André4Jérôme Boutang5LICIT-ECO7 Lab, ENTPE, Université Gustave Eiffel, 69675 Bron, FranceLICIT-ECO7 Lab, ENTPE, Université Gustave Eiffel, 69675 Bron, FranceLICIT-ECO7 Lab, ENTPE, Université Gustave Eiffel, 69675 Bron, FranceCitepa, 42 rue de Paradis, 75010 Paris, FranceCitepa, 42 rue de Paradis, 75010 Paris, FranceCitepa, 42 rue de Paradis, 75010 Paris, FranceOver the last two decades, mobile phone data have appeared to be a promising data source for mobility analysis. The structure, abundance, and accessibility of call detail records (CDRs) make them particularly suitable for such use. However, their exploitation is often limited to estimating origin–destination matrices of a restricted part of the population: regular travellers. Although these studies provide valuable information for policymakers, their scope remains limited to this subpopulation analysis. In the present work, we develop a collective mobility reconstruction method adapted to nonregular travellers. The method relies on the notion of the detour ratio, which makes it robust to the lack of mobile phone data as well as its application to large instances (large and dense telecommunication networks). It is used to conduct a longitudinal analysis of the macroscopic mobility patterns in Santiago de Cali, Colombia, thanks to call detail data shared by communication provider CLARO as part of a research project conducted by Citepa, Paris, the Green City Big Data Project.https://www.mdpi.com/2673-7590/3/1/15mobile phone datacall detail recordsmobility patternsmacroscopic mobility reconstructioncollective mobility reconstructiontotal travelled distances |
| spellingShingle | Manon Seppecher Ludovic Leclercq Angelo Furno Thamara Vieira da Rocha Jean-Marc André Jérôme Boutang Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data Future Transportation mobile phone data call detail records mobility patterns macroscopic mobility reconstruction collective mobility reconstruction total travelled distances |
| title | Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data |
| title_full | Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data |
| title_fullStr | Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data |
| title_full_unstemmed | Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data |
| title_short | Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data |
| title_sort | identification of aggregate urban mobility patterns of nonregular travellers from mobile phone data |
| topic | mobile phone data call detail records mobility patterns macroscopic mobility reconstruction collective mobility reconstruction total travelled distances |
| url | https://www.mdpi.com/2673-7590/3/1/15 |
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