TelematiV1, Ncbi, Checkpoint, bibRecord, 000A64

Quantifying the benefits of vehicle pooling with shareability networks

Identifieur interne : 000A64 ( Ncbi/Checkpoint ); précédent : 000A63; suivant : 000A65

Quantifying the benefits of vehicle pooling with shareability networks

Auteurs : Paolo Santi [Italie] ; Giovanni Resta [Italie] ; Michael Szell ; Stanislav Sobolevsky ; Steven H. Strogatz ; Carlo Ratti

Source :

Proceedings of the National Academy of Sciences of the United States of America [ 0027-8424 ] ; 2014.

RBID : PMC:4169909

Abstract

Significance

Recent advances in information technologies have increased our participation in “sharing economies,” where applications that allow networked, real-time data exchange facilitate the sharing of living spaces, equipment, or vehicles with others. However, the impact of large-scale sharing on sustainability is not clear, and a framework to assess its benefits quantitatively is missing. For this purpose, we propose the method of shareability networks, which translates spatio-temporal sharing problems into a graph-theoretic framework that provides efficient solutions. Applying this method to a dataset of 150 million taxi trips in New York City, our simulations reveal the vast potential of a new taxi system in which trips are routinely shareable while keeping passenger discomfort low in terms of prolonged travel time.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4169909

DOI: 10.1073/pnas.1403657111
PubMed: 25197046
PubMed Central: 4169909

Affiliations:

Italie

Links to Exploration step

PMC:4169909

Le document en format XML

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<front><div type="abstract" xml:lang="en"><title>Significance</title>
<p>Recent advances in information technologies have increased our participation in “sharing economies,” where applications that allow networked, real-time data exchange facilitate the sharing of living spaces, equipment, or vehicles with others. However, the impact of large-scale sharing on sustainability is not clear, and a framework to assess its benefits quantitatively is missing. For this purpose, we propose the method of shareability networks, which translates spatio-temporal sharing problems into a graph-theoretic framework that provides efficient solutions. Applying this method to a dataset of 150 million taxi trips in New York City, our simulations reveal the vast potential of a new taxi system in which trips are routinely shareable while keeping passenger discomfort low in terms of prolonged travel time.</p>
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Quantifying the benefits of vehicle pooling with shareability networks

Quantifying the benefits of vehicle pooling with shareability networks

Source :

Abstract

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Links to Exploration step

Le document en format XML

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