Opportunistic Ride Sharing via Whereabouts Analysis

Smart phones and social networking tools allow to collect large-scale data about mobility habits of people. These data can support advanced forms of sharing, coordination and cooperation possibly able to reduce the overall demand for mobility. The authors present a methodology, based on the extraction of suitable information from mobility traces, to identify rides along the same trajectories that are amenable for ride sharing. Results on a real dataset show that, assuming users are willing to share rides and tolerate 1Km detours, about 60% of trips could be saved.

  • Record URL:
  • Supplemental Notes:
    • Copyright © 2015, IEEE.
  • Authors:
    • Bicocchi, Nicola
    • Mamei, Marco
    • Sassi, Andrea
    • Zambonelli, Franco
  • Publication Date: 2015

Language

  • English

Media Info

  • Media Type: Web
  • Features: Figures; References;
  • Pagination: 875-881

Subject/Index Terms

Filing Info

  • Accession Number: 01614127
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 2 2016 3:17PM