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Scaling Law of Urban Ride Sharing

Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trip...

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Autores principales: Tachet, R., Sagarra, O., Santi, P., Resta, G., Szell, M., Strogatz, S. H., Ratti, C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337932/
https://www.ncbi.nlm.nih.gov/pubmed/28262743
http://dx.doi.org/10.1038/srep42868
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author Tachet, R.
Sagarra, O.
Santi, P.
Resta, G.
Szell, M.
Strogatz, S. H.
Ratti, C.
author_facet Tachet, R.
Sagarra, O.
Santi, P.
Resta, G.
Szell, M.
Strogatz, S. H.
Ratti, C.
author_sort Tachet, R.
collection PubMed
description Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trips in New York City, San Francisco, Singapore, and Vienna, we compute the shareability curves for each city, and find that a natural rescaling collapses them onto a single, universal curve. We explain this scaling law theoretically with a simple model that predicts the potential for ride sharing in any city, using a few basic urban quantities and no adjustable parameters. Accurate extrapolations of this type will help planners, transportation companies, and society at large to shape a sustainable path for urban growth.
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spelling pubmed-53379322017-03-08 Scaling Law of Urban Ride Sharing Tachet, R. Sagarra, O. Santi, P. Resta, G. Szell, M. Strogatz, S. H. Ratti, C. Sci Rep Article Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trips in New York City, San Francisco, Singapore, and Vienna, we compute the shareability curves for each city, and find that a natural rescaling collapses them onto a single, universal curve. We explain this scaling law theoretically with a simple model that predicts the potential for ride sharing in any city, using a few basic urban quantities and no adjustable parameters. Accurate extrapolations of this type will help planners, transportation companies, and society at large to shape a sustainable path for urban growth. Nature Publishing Group 2017-03-06 /pmc/articles/PMC5337932/ /pubmed/28262743 http://dx.doi.org/10.1038/srep42868 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Tachet, R.
Sagarra, O.
Santi, P.
Resta, G.
Szell, M.
Strogatz, S. H.
Ratti, C.
Scaling Law of Urban Ride Sharing
title Scaling Law of Urban Ride Sharing
title_full Scaling Law of Urban Ride Sharing
title_fullStr Scaling Law of Urban Ride Sharing
title_full_unstemmed Scaling Law of Urban Ride Sharing
title_short Scaling Law of Urban Ride Sharing
title_sort scaling law of urban ride sharing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337932/
https://www.ncbi.nlm.nih.gov/pubmed/28262743
http://dx.doi.org/10.1038/srep42868
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