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Statistical patterns of human mobility in emerging Bicycle Sharing Systems
The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to “photograph” the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distan...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854355/ https://www.ncbi.nlm.nih.gov/pubmed/29543832 http://dx.doi.org/10.1371/journal.pone.0193795 |
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author | Chang, Xiangyu Shen, Jingzhou Lu, Xiaoling Huang, Shuai |
author_facet | Chang, Xiangyu Shen, Jingzhou Lu, Xiaoling Huang, Shuai |
author_sort | Chang, Xiangyu |
collection | PubMed |
description | The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to “photograph” the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distance trip supplement for public transportations and private vehicles. A unique value of the bike flow data generated by these BSSs is to understand the human mobility in a short-distance trip. This understanding of the population on short-distance trip is lacking, limiting our capacity in management and operation of BSSs. Many existing operations research and management methods for BSS impose assumptions that emphasize statistical simplicity and homogeneity. Therefore, a deep understanding of the statistical patterns embedded in the bike flow data is an urgent and overriding issue to inform decision-makings for a variety of problems including traffic prediction, station placement, bike reallocation, and anomaly detection. In this paper, we aim to conduct a comprehensive analysis of the bike flow data using two large datasets collected in Chicago and Hangzhou over months. Our analysis reveals intrinsic structures of the bike flow data and regularities in both spatial and temporal scales such as a community structure and a taxonomy of the eigen-bike-flows. |
format | Online Article Text |
id | pubmed-5854355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58543552018-03-28 Statistical patterns of human mobility in emerging Bicycle Sharing Systems Chang, Xiangyu Shen, Jingzhou Lu, Xiaoling Huang, Shuai PLoS One Research Article The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to “photograph” the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distance trip supplement for public transportations and private vehicles. A unique value of the bike flow data generated by these BSSs is to understand the human mobility in a short-distance trip. This understanding of the population on short-distance trip is lacking, limiting our capacity in management and operation of BSSs. Many existing operations research and management methods for BSS impose assumptions that emphasize statistical simplicity and homogeneity. Therefore, a deep understanding of the statistical patterns embedded in the bike flow data is an urgent and overriding issue to inform decision-makings for a variety of problems including traffic prediction, station placement, bike reallocation, and anomaly detection. In this paper, we aim to conduct a comprehensive analysis of the bike flow data using two large datasets collected in Chicago and Hangzhou over months. Our analysis reveals intrinsic structures of the bike flow data and regularities in both spatial and temporal scales such as a community structure and a taxonomy of the eigen-bike-flows. Public Library of Science 2018-03-15 /pmc/articles/PMC5854355/ /pubmed/29543832 http://dx.doi.org/10.1371/journal.pone.0193795 Text en © 2018 Chang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Chang, Xiangyu Shen, Jingzhou Lu, Xiaoling Huang, Shuai Statistical patterns of human mobility in emerging Bicycle Sharing Systems |
title | Statistical patterns of human mobility in emerging Bicycle Sharing Systems |
title_full | Statistical patterns of human mobility in emerging Bicycle Sharing Systems |
title_fullStr | Statistical patterns of human mobility in emerging Bicycle Sharing Systems |
title_full_unstemmed | Statistical patterns of human mobility in emerging Bicycle Sharing Systems |
title_short | Statistical patterns of human mobility in emerging Bicycle Sharing Systems |
title_sort | statistical patterns of human mobility in emerging bicycle sharing systems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854355/ https://www.ncbi.nlm.nih.gov/pubmed/29543832 http://dx.doi.org/10.1371/journal.pone.0193795 |
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