Reply to Lopez et al.: Sustainable implementation of taxi sharing requires understanding systemic effects (Articolo in rivista)

Type
Label
  • Reply to Lopez et al.: Sustainable implementation of taxi sharing requires understanding systemic effects (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1073/pnas.1421300112 (literal)
Alternative label
  • Santi P.; Resta G.; Szell M.; Sobolevsky S.; Strogatz S.H.; Ratti C. (2014)
    Reply to Lopez et al.: Sustainable implementation of taxi sharing requires understanding systemic effects
    in Proceedings of the National Academy of Sciences of the United States of America
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Santi P.; Resta G.; Szell M.; Sobolevsky S.; Strogatz S.H.; Ratti C. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84919949766&partnerID=q2rCbXpz (literal)
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  • 111 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 51 (literal)
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Senseable City Laboratory, Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, 02139, United States; Istituto di Informatica e Telematica del Consiglio Nazionale Delle Ricerche, Pisa, 56124, Italy; Department of Mathematics, Cornell University, Ithaca, NY, 14853, United States (literal)
Titolo
  • Reply to Lopez et al.: Sustainable implementation of taxi sharing requires understanding systemic effects (literal)
Abstract
  • 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. suggested by Lopez et al. (2) and in our report (1) go exactly along this direction. (literal)
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