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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...

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Detalles Bibliográficos
Autores principales: Chang, Xiangyu, Shen, Jingzhou, Lu, Xiaoling, Huang, Shuai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
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.
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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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