ArticlePloS one2019
Human mobility in bike-sharing systems: Structure of local and non-local dynamics.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Article
- Intermunicipal travel networks of Mexico during the COVID-19 pandemic.Scientific reports · 2023Article
- Temporal visitation patterns of points of interest in cities on a planetary scale: a network science and machine learning approach.Scientific reports · 2023Article
- Activity of vehicles in the bus rapid transit system Metrobús in Mexico City.Scientific reports · 2022Article
- Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London.PloS one · 2021Article
- Networks and long-range mobility in cities: A study of more than one billion taxi trips in New York City.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The understanding of human mobility patterns in different transportation modes is an interdisciplinary research field with a direct impact in aspects as varied as urban planning, traffic optimization, sustainability, the reduction of operating costs as well as the mitigation of pollution in urban areas. In this paper, we study the global activity of users in bike-sharing systems operating in the cities of Chicago and New York. For this transportation mode, we explore the temporal and spatial characteristics of the mobility of cyclists. In particular, through the analysis of origin-destination matrices, we characterize the spatial structure of the displacements of users. We apply a mobility model for the global activity of the system that classifies the displacements between stations in local and non-local transitions. In local transitions, cyclists move in a region around each station whereas, in the non-local case, bike users travel with long-range displacements in a similar way to Lévy flights. We reproduce the spatial dynamics by using Monte Carlo simulations. The obtained results are similar to the observed in real data and reveal that the model implemented captures important characteristics of the global spatial dynamics in the systems analyzed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.