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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Quantifying the benefits of vehicle pooling with shareability networks</title><author><name sortKey="Santi, Paolo" sort="Santi, Paolo" uniqKey="Santi P" first="Paolo" last="Santi">Paolo Santi</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation><affiliation><nlm:aff wicri:cut="; and" id="aff2">Istituto di Informatica e Telematica del<institution>Consiglio Nazionale delle Ricerche</institution>, 56124 Pisa,<country>Italy</country></nlm:aff></affiliation></author><author><name sortKey="Resta, Giovanni" sort="Resta, Giovanni" uniqKey="Resta G" first="Giovanni" last="Resta">Giovanni Resta</name><affiliation><nlm:aff wicri:cut="; and" id="aff2">Istituto di Informatica e Telematica del<institution>Consiglio Nazionale delle Ricerche</institution>, 56124 Pisa,<country>Italy</country></nlm:aff></affiliation></author><author><name sortKey="Szell, Michael" sort="Szell, Michael" uniqKey="Szell M" first="Michael" last="Szell">Michael Szell</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation></author><author><name sortKey="Sobolevsky, Stanislav" sort="Sobolevsky, Stanislav" uniqKey="Sobolevsky S" first="Stanislav" last="Sobolevsky">Stanislav Sobolevsky</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation></author><author><name sortKey="Strogatz, Steven H" sort="Strogatz, Steven H" uniqKey="Strogatz S" first="Steven H." last="Strogatz">Steven H. Strogatz</name><affiliation><nlm:aff id="aff3">Department of Mathematics,<institution>Cornell University</institution>, Ithaca,<addr-line>NY</addr-line> 14853</nlm:aff></affiliation></author><author><name sortKey="Ratti, Carlo" sort="Ratti, Carlo" uniqKey="Ratti C" first="Carlo" last="Ratti">Carlo Ratti</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25197046</idno><idno type="pmc">4169909</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4169909</idno><idno type="RBID">PMC:4169909</idno><idno type="doi">10.1073/pnas.1403657111</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000398</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000398</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Quantifying the benefits of vehicle pooling with shareability networks</title><author><name sortKey="Santi, Paolo" sort="Santi, Paolo" uniqKey="Santi P" first="Paolo" last="Santi">Paolo Santi</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation><affiliation><nlm:aff wicri:cut="; and" id="aff2">Istituto di Informatica e Telematica del<institution>Consiglio Nazionale delle Ricerche</institution>, 56124 Pisa,<country>Italy</country></nlm:aff></affiliation></author><author><name sortKey="Resta, Giovanni" sort="Resta, Giovanni" uniqKey="Resta G" first="Giovanni" last="Resta">Giovanni Resta</name><affiliation><nlm:aff wicri:cut="; and" id="aff2">Istituto di Informatica e Telematica del<institution>Consiglio Nazionale delle Ricerche</institution>, 56124 Pisa,<country>Italy</country></nlm:aff></affiliation></author><author><name sortKey="Szell, Michael" sort="Szell, Michael" uniqKey="Szell M" first="Michael" last="Szell">Michael Szell</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation></author><author><name sortKey="Sobolevsky, Stanislav" sort="Sobolevsky, Stanislav" uniqKey="Sobolevsky S" first="Stanislav" last="Sobolevsky">Stanislav Sobolevsky</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation></author><author><name sortKey="Strogatz, Steven H" sort="Strogatz, Steven H" uniqKey="Strogatz S" first="Steven H." last="Strogatz">Steven H. Strogatz</name><affiliation><nlm:aff id="aff3">Department of Mathematics,<institution>Cornell University</institution>, Ithaca,<addr-line>NY</addr-line> 14853</nlm:aff></affiliation></author><author><name sortKey="Ratti, Carlo" sort="Ratti, Carlo" uniqKey="Ratti C" first="Carlo" last="Ratti">Carlo Ratti</name><affiliation><nlm:aff id="aff1">Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</nlm:aff></affiliation></author></analytic><series><title level="j">Proceedings of the National Academy of Sciences of the United States of America</title><idno type="ISSN">0027-8424</idno><idno type="eISSN">1091-6490</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><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></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Proc Natl Acad Sci U S A</journal-id><journal-id journal-id-type="iso-abbrev">Proc. Natl. Acad. Sci. U.S.A</journal-id><journal-id journal-id-type="hwp">pnas</journal-id><journal-id journal-id-type="pmc">pnas</journal-id><journal-id journal-id-type="publisher-id">PNAS</journal-id><journal-title-group><journal-title>Proceedings of the National Academy of Sciences of the United States of America</journal-title></journal-title-group><issn pub-type="ppub">0027-8424</issn><issn pub-type="epub">1091-6490</issn><publisher><publisher-name>National Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25197046</article-id><article-id pub-id-type="pmc">4169909</article-id><article-id pub-id-type="publisher-id">201403657</article-id><article-id pub-id-type="doi">10.1073/pnas.1403657111</article-id><article-categories><subj-group subj-group-type="hwp-journal-coll"><subject>9</subject></subj-group><subj-group subj-group-type="heading"><subject>Physical Sciences</subject><subj-group><subject>Computer Sciences</subject></subj-group></subj-group><subj-group subj-group-type="heading"><subject>Social Sciences</subject><subj-group><subject>Sustainability Science</subject></subj-group></subj-group><series-title>From the Cover</series-title></article-categories><title-group><article-title>Quantifying the benefits of vehicle pooling with shareability networks</article-title><alt-title alt-title-type="short">Vehicle pooling with shareability networks</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Santi</surname><given-names>Paolo</given-names></name><xref ref-type="aff" rid="aff1"><sup>a</sup></xref><xref ref-type="aff" rid="aff2"><sup>b</sup></xref></contrib><contrib contrib-type="author"><name><surname>Resta</surname><given-names>Giovanni</given-names></name><xref ref-type="aff" rid="aff2"><sup>b</sup></xref></contrib><contrib contrib-type="author"><name><surname>Szell</surname><given-names>Michael</given-names></name><xref ref-type="aff" rid="aff1"><sup>a</sup></xref><xref ref-type="corresp" rid="cor1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Sobolevsky</surname><given-names>Stanislav</given-names></name><xref ref-type="aff" rid="aff1"><sup>a</sup></xref></contrib><contrib contrib-type="author"><name><surname>Strogatz</surname><given-names>Steven H.</given-names></name><xref ref-type="aff" rid="aff3"><sup>c</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ratti</surname><given-names>Carlo</given-names></name><xref ref-type="aff" rid="aff1"><sup>a</sup></xref></contrib><aff id="aff1"><sup>a</sup>Senseable City Laboratory,<institution>Massachusetts Institute of Technology</institution>, Cambridge,<addr-line>MA</addr-line> 02139;</aff><aff id="aff2"><sup>b</sup>Istituto di Informatica e Telematica del<institution>Consiglio Nazionale delle Ricerche</institution>, 56124 Pisa,<country>Italy</country>; and</aff><aff id="aff3"><sup>c</sup>Department of Mathematics,<institution>Cornell University</institution>, Ithaca,<addr-line>NY</addr-line> 14853</aff></contrib-group><author-notes><corresp id="cor1"><sup>1</sup>To whom correspondence should be addressed. Email: <email>mszell@mit.edu</email>.</corresp><fn fn-type="edited-by"><p>Edited<xref ref-type="fn" rid="fn1">*</xref> by Michael F. Goodchild, University of California, Santa Barbara, CA, and approved July 25, 2014 (received for review March 3, 2014)</p></fn><fn fn-type="con"><p>Author contributions: P.S., G.R., M.S., S.S., and C.R. designed research; P.S., G.R., M.S., and S.S. performed research; P.S., G.R., M.S., S.S., and C.R. contributed new reagents/analytic tools; P.S., G.R., M.S., S.S., S.H.S., and C.R. analyzed data; and P.S., M.S., S.S., S.H.S., and C.R. wrote the paper.</p></fn></author-notes><pub-date pub-type="ppub"><day>16</day><month>9</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>2</day><month>9</month><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>2</day><month>9</month><year>2014</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
<volume>111</volume><issue>37</issue><fpage>13290</fpage><lpage>13294</lpage><permissions><license license-type="open-access"><license-p>Freely available online through the PNAS open access option.</license-p></license></permissions><self-uri xlink:title="pdf" xlink:type="simple" xlink:href="pnas.201403657.pdf"></self-uri><abstract abstract-type="executive-summary"><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></abstract><abstract><p>Taxi services are a vital part of urban transportation, and a considerable contributor to traffic congestion and air pollution causing substantial adverse effects on human health. Sharing taxi trips is a possible way of reducing the negative impact of taxi services on cities, but this comes at the expense of passenger discomfort quantifiable in terms of a longer travel time. Due to computational challenges, taxi sharing has traditionally been approached on small scales, such as within airport perimeters, or with dynamical ad hoc heuristics. However, a mathematical framework for the systematic understanding of the tradeoff between collective benefits of sharing and individual passenger discomfort is lacking. Here we introduce the notion of shareability network, which allows us to model the collective benefits of sharing as a function of passenger inconvenience, and to efficiently compute optimal sharing strategies on massive datasets. We apply this framework to a dataset of millions of taxi trips taken in New York City, showing that with increasing but still relatively low passenger discomfort, cumulative trip length can be cut by 40% or more. This benefit comes with reductions in service cost, emissions, and with split fares, hinting toward a wide passenger acceptance of such a shared service. Simulation of a realistic online system demonstrates the feasibility of a shareable taxi service in New York City. Shareability as a function of trip density saturates fast, suggesting effectiveness of the taxi sharing system also in cities with much sparser taxi fleets or when willingness to share is low.</p></abstract><kwd-group><kwd>carpooling</kwd><kwd>human mobility</kwd><kwd>urban computing</kwd><kwd>maximum matching</kwd></kwd-group><counts><page-count count="5"></page-count></counts></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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