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Taxi vs. demand responsive shared transport systems: An agent-based simulation approach

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Listed:
  • Inturri, Giuseppe
  • Giuffrida, Nadia
  • Ignaccolo, Matteo
  • Le Pira, Michela
  • Pluchino, Alessandro
  • Rapisarda, Andrea
  • D'Angelo, Riccardo

Abstract

Public transport in urban and suburban areas is not always able to meet population's need of accessibility to jobs, education, health and other opportunities in terms of routes and frequencies; therefore, those who do not own a private vehicle, or who cannot afford individual public transport (e.g. taxis), are often in a condition of social exclusion. Taking advantages of new ICT tools and facilities, Demand Responsive Shared Transport (DRST) services can provide “on demand” transport gathering ride bookings of different users and routing a fleet of vehicles to satisfy passengers' needs while minimizing the cost for the operator.

Suggested Citation

  • Inturri, Giuseppe & Giuffrida, Nadia & Ignaccolo, Matteo & Le Pira, Michela & Pluchino, Alessandro & Rapisarda, Andrea & D'Angelo, Riccardo, 2021. "Taxi vs. demand responsive shared transport systems: An agent-based simulation approach," Transport Policy, Elsevier, vol. 103(C), pages 116-126.
    • Handle: RePEc:eee:trapol:v:103:y:2021:i:c:p:116-126
    DOI: 10.1016/j.tranpol.2021.01.002
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    References listed on IDEAS

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    1. Inturri, Giuseppe & Le Pira, Michela & Giuffrida, Nadia & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea & D'Angelo, Riccardo, 2019. "Multi-agent simulation for planning and designing new shared mobility services," Research in Transportation Economics, Elsevier, vol. 73(C), pages 34-44.
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    3. Zhou, Yefang & Sato, Hitomi & Yamamoto, Toshiyuki, 2023. "Resourcing idle privately owned autonomous electric vehicles: System design and simulation for ride-sharing in residential areas of the aging in Japan," Transport Policy, Elsevier, vol. 143(C), pages 46-57.

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